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| cloud natural language api: Pragmatic AI Noah Gift, 2018-07-12 Master Powerful Off-the-Shelf Business Solutions for AI and Machine Learning Pragmatic AI will help you solve real-world problems with contemporary machine learning, artificial intelligence, and cloud computing tools. Noah Gift demystifies all the concepts and tools you need to get results—even if you don’t have a strong background in math or data science. Gift illuminates powerful off-the-shelf cloud offerings from Amazon, Google, and Microsoft, and demonstrates proven techniques using the Python data science ecosystem. His workflows and examples help you streamline and simplify every step, from deployment to production, and build exceptionally scalable solutions. As you learn how machine language (ML) solutions work, you’ll gain a more intuitive understanding of what you can achieve with them and how to maximize their value. Building on these fundamentals, you’ll walk step-by-step through building cloud-based AI/ML applications to address realistic issues in sports marketing, project management, product pricing, real estate, and beyond. Whether you’re a business professional, decision-maker, student, or programmer, Gift’s expert guidance and wide-ranging case studies will prepare you to solve data science problems in virtually any environment. Get and configure all the tools you’ll need Quickly review all the Python you need to start building machine learning applications Master the AI and ML toolchain and project lifecycle Work with Python data science tools such as IPython, Pandas, Numpy, Juypter Notebook, and Sklearn Incorporate a pragmatic feedback loop that continually improves the efficiency of your workflows and systems Develop cloud AI solutions with Google Cloud Platform, including TPU, Colaboratory, and Datalab services Define Amazon Web Services cloud AI workflows, including spot instances, code pipelines, boto, and more Work with Microsoft Azure AI APIs Walk through building six real-world AI applications, from start to finish Register your book for convenient access to downloads, updates, and/or corrections as they become available. See inside book for details. |
| cloud natural language api: NATURAL LANGUAGE PROCESSING Dr. Praveen Kumar Mannepalli, Mrs. Ayesha Khan, Mrs. Parul Khatri, Mrs. Harshita Chourasia, 2024-03-15 There is a growing need for the intelligent processing of unstructured text data, which includes the extraction of various forms of information from it, since the amount of unstructured text data that mankind creates generally & on the Internet continues to evolve. In order to address a variety of higher-level language issues, the goal of my study is to create learning models that are capable of independently producing representations of human language, namely its structure and meaning. my is for the purpose of my thesis. When it comes to the delivery of technologies in the field of natural language processing (NLP), a significant amount of progress has been made. These technologies include the extraction of information from large amounts of unstructured data on the internet, the analysis of sentiment in social networks, and the grammatical analysis of essays for the purpose of grading. The creation of universal & scalable algorithms that are capable of jointly solving these problems & learning the appropriate intermediate representations of the linguistic units involved is that which is one of the aims of natural language processing. Standard ways to achieving this objective, on the other hand, suffer from two basic deficiencies. |
| cloud natural language api: Handbook of Cloud Computing Nayyar Dr. Anand, 2019-09-20 Great POSSIBILITIES and high future prospects to become ten times folds in the near FUTUREKey features Comprehensively gives clear picture of current state-of-the-art aspect of cloud computing by elaborating terminologies, models and other related terms. Enlightens all major players in Cloud Computing industry providing services in terms of SaaS, PaaS and IaaS. Highlights Cloud Computing Simulators, Security Aspect and Resource Allocation. In-depth presentation with well-illustrated diagrams and simple to understand technical concepts of cloud. Description The book e;Handbook of Cloud Computinge; provides the latest and in-depth information of this relatively new and another platform for scientific computing which has great possibilities and high future prospects to become ten folds in near future. The book covers in comprehensive manner all aspects and terminologies associated with cloud computing like SaaS, PaaS and IaaS and also elaborates almost every cloud computing service model.The book highlights several other aspects of cloud computing like Security, Resource allocation, Simulation Platforms and futuristic trend i.e. Mobile cloud computing. The book will benefit all the readers with all in-depth technical information which is required to understand current and futuristic concepts of cloud computing. No prior knowledge of cloud computing or any of its related technology is required in reading this book. What will you learn Cloud Computing, Virtualisation Software as a Service, Platform as a Service, Infrastructure as a Service Data in Cloud and its Security Cloud Computing - Simulation, Mobile Cloud Computing Specific Cloud Service Models Resource Allocation in Cloud Computing Who this book is for Students of Polytechnic Diploma Classes- Computer Science/ Information Technology Graduate Students- Computer Science/ CSE / IT/ Computer Applications Master Class Students-Msc (CS/IT)/ MCA/ M.Phil, M.Tech, M.S. Researcher's-Ph.D Research Scholars doing work in Virtualization, Cloud Computing and Cloud Security Industry Professionals- Preparing for Certifications, Implementing Cloud Computing and even working on Cloud Security Table of contents1. Introduction to Cloud Computing2. Virtualisation3. Software as a Service4. Platform as a Service5. Infrastructure as a Service6. Data in Cloud7. Cloud Security 8. Cloud Computing - Simulation9. Specific Cloud Service Models10. Resource Allocation in Cloud Computing11. Mobile Cloud Computing About the authorDr. Anand Nayyar received Ph.D (Computer Science) in Wireless Sensor Networks and Swarm Intelligence. Presently he is working in Graduate School, Duy Tan University, Da Nang, Vietnam. He has total of fourteen Years of Teaching, Research and Consultancy experience with more than 250 Research Papers in various International Conferences and highly reputed journals. He is certified Professional with more than 75 certificates and member of 50 Professional Organizations. He is acting as e;ACM DISTINGUISHED SPEAKERe; |
| cloud natural language api: Machine Learning in the Cloud: Comparing Google Cloud, AWS, and Azure APIs Peter Jones, 2024-10-13 Unlock the full potential of machine learning with Machine Learning in the Cloud: Comparing Google Cloud, AWS, and Azure APIs. This essential guide meticulously navigates through the intricate world of cloud-based ML APIs across the leading platforms—Google Cloud, AWS, and Azure. Whether you're a software developer, data scientist, IT professional, or business strategist, this book equips you with the knowledge to make informed decisions about implementing and managing these powerful tools in your projects. Dive deep into a comprehensive analysis and comparison of text processing, image recognition, speech recognition, and custom model building services offered by these giants. Understand the ins and outs of setting up, configuring, and optimizing these APIs for performance and scalability. Explore chapters dedicated to security, compliance, and real-life success stories that demonstrate the transformative impact of cloud-based ML across various industries. With practical guides, strategic insights, and current industry standards, this book is your roadmap to mastering cloud machine learning APIs, paving the way for innovative solutions that enhance competitiveness and efficiency. Embrace the future of artificial intelligence with this expertly crafted resource at your fingertips. |
| cloud natural language api: Google Cloud AI Services Quick Start Guide Arvind Ravulavaru, 2018-05-30 Leverage the power of various Google Cloud AI Services by building a smart web application using MEAN Stack Key Features Start working with the Google Cloud Platform and the AI services it offers Build smart web applications by combining the power of Google Cloud AI services and the MEAN stack Build a web-based dashboard of smart applications that perform language processing, translation, and computer vision on the cloud Book Description Cognitive services are the new way of adding intelligence to applications and services. Now we can use Artificial Intelligence as a service that can be consumed by any application or other service, to add smartness and make the end result more practical and useful. Google Cloud AI enables you to consume Artificial Intelligence within your applications, from a REST API. Text, video and speech analysis are among the powerful machine learning features that can be used. This book is the easiest way to get started with the Google Cloud AI services suite and open up the world of smarter applications. This book will help you build a Smart Exchange, a forum application that will let you upload videos, images and perform text to speech conversions and translation services. You will use the power of Google Cloud AI Services to make our simple forum application smart by validating the images, videos, and text provided by users to Google Cloud AI Services and make sure the content which is uploaded follows the forum standards, without a human curator involvement. You will learn how to work with the Vision API, Video Intelligence API, Speech Recognition API, Cloud Language Process, and Cloud Translation API services to make your application smarter. By the end of this book, you will have a strong understanding of working with Google Cloud AI Services, and be well on the way to building smarter applications. What you will learn Understand Google Cloud Platform and its Cloud AI services Explore the Google ML Services Work with an Angular 5 MEAN stack application Integrate Vision API, Video Intelligence API for computer vision Be ready for conversational experiences with the Speech Recognition API, Cloud Language Process and Cloud Translation API services Build a smart web application that uses the power of Google Cloud AI services to make apps smarter Who this book is for This book is ideal for data professionals and web developers who want to use the power of Google Cloud AI services in their projects, without the going through the pain of mastering machine learning for images, videos and text. Some familiarity with the Google Cloud Platform will be helpful. |
| cloud natural language api: Natural Language Processing with Python Steven Bird, Ewan Klein, Edward Loper, 2009-06-12 This book offers a highly accessible introduction to natural language processing, the field that supports a variety of language technologies, from predictive text and email filtering to automatic summarization and translation. With it, you'll learn how to write Python programs that work with large collections of unstructured text. You'll access richly annotated datasets using a comprehensive range of linguistic data structures, and you'll understand the main algorithms for analyzing the content and structure of written communication. Packed with examples and exercises, Natural Language Processing with Python will help you: Extract information from unstructured text, either to guess the topic or identify named entities Analyze linguistic structure in text, including parsing and semantic analysis Access popular linguistic databases, including WordNet and treebanks Integrate techniques drawn from fields as diverse as linguistics and artificial intelligence This book will help you gain practical skills in natural language processing using the Python programming language and the Natural Language Toolkit (NLTK) open source library. If you're interested in developing web applications, analyzing multilingual news sources, or documenting endangered languages -- or if you're simply curious to have a programmer's perspective on how human language works -- you'll find Natural Language Processing with Python both fascinating and immensely useful. |
| cloud natural language api: The Development of Natural Language Processing China Info & Comm Tech Grp Corp, 2021-06-09 This book is a part of the Blue Book series “Research on the Development of Electronic Information Engineering Technology in China”, which explores the cutting edge of natural language processing (NLP) studies. The research objects of natural language processing are evolved from words, phrases, and sentences to text, and research directions are from language analysis, language understanding, language generation, knowledge graphs, machine translation, to deep semantic understanding, and beyond. This is in line with the development trend of applications. And for another typical NLP application machine translation, from text translation, to voice and image translation, now simultaneous interpretation, progress of technology makes the application of machine translation deeper and wider into diverse industries. This book is intended for researchers and industrial staffs who have been following the current situation and future trends of the natural language processing. Meanwhile, it also bears high value of reference for experts, scholars, and technical and engineering managers of different levels and different fields. |
| cloud natural language api: Mastering Google Cloud Platform Cybellium Ltd, 2023-09-06 Cybellium Ltd is dedicated to empowering individuals and organizations with the knowledge and skills they need to navigate the ever-evolving computer science landscape securely and learn only the latest information available on any subject in the category of computer science including: - Information Technology (IT) - Cyber Security - Information Security - Big Data - Artificial Intelligence (AI) - Engineering - Robotics - Standards and compliance Our mission is to be at the forefront of computer science education, offering a wide and comprehensive range of resources, including books, courses, classes and training programs, tailored to meet the diverse needs of any subject in computer science. Visit https://www.cybellium.com for more books. |
| cloud natural language api: Practical Natural Language Processing Sowmya Vajjala, Bodhisattwa Majumder, Anuj Gupta, Harshit Surana, 2020-06-17 Many books and courses tackle natural language processing (NLP) problems with toy use cases and well-defined datasets. But if you want to build, iterate, and scale NLP systems in a business setting and tailor them for particular industry verticals, this is your guide. Software engineers and data scientists will learn how to navigate the maze of options available at each step of the journey. Through the course of the book, authors Sowmya Vajjala, Bodhisattwa Majumder, Anuj Gupta, and Harshit Surana will guide you through the process of building real-world NLP solutions embedded in larger product setups. You’ll learn how to adapt your solutions for different industry verticals such as healthcare, social media, and retail. With this book, you’ll: Understand the wide spectrum of problem statements, tasks, and solution approaches within NLP Implement and evaluate different NLP applications using machine learning and deep learning methods Fine-tune your NLP solution based on your business problem and industry vertical Evaluate various algorithms and approaches for NLP product tasks, datasets, and stages Produce software solutions following best practices around release, deployment, and DevOps for NLP systems Understand best practices, opportunities, and the roadmap for NLP from a business and product leader’s perspective |
| cloud natural language api: Natural Language Processing with Java Cookbook Richard M. Reese, 2019-04-25 A problem-solution guide to encounter various NLP tasks utilizing Java open source libraries and cloud-based solutions Key FeaturesPerform simple-to-complex NLP text processing tasks using modern Java libraries Extract relationships between different text complexities using a problem-solution approach Utilize cloud-based APIs to perform machine translation operationsBook Description Natural Language Processing (NLP) has become one of the prime technologies for processing very large amounts of unstructured data from disparate information sources. This book includes a wide set of recipes and quick methods that solve challenges in text syntax, semantics, and speech tasks. At the beginning of the book, you'll learn important NLP techniques, such as identifying parts of speech, tagging words, and analyzing word semantics. You will learn how to perform lexical analysis and use machine learning techniques to speed up NLP operations. With independent recipes, you will explore techniques for customizing your existing NLP engines/models using Java libraries such as OpenNLP and the Stanford NLP library. You will also learn how to use NLP processing features from cloud-based sources, including Google and Amazon’s AWS. You will master core tasks, such as stemming, lemmatization, part-of-speech tagging, and named entity recognition. You will also learn about sentiment analysis, semantic text similarity, language identification, machine translation, and text summarization. By the end of this book, you will be ready to become a professional NLP expert using a problem-solution approach to analyze any sort of text, sentences, or semantic words. What you will learnExplore how to use tokenizers in NLP processing Implement NLP techniques in machine learning and deep learning applications Identify sentences within the text and learn how to train specialized NER models Learn how to classify documents and perform sentiment analysis Find semantic similarities between text elements and extract text from a variety of sources Preprocess text from a variety of data sources Learn how to identify and translate languagesWho this book is for This book is for data scientists, NLP engineers, and machine learning developers who want to perform their work on linguistic applications faster with the use of popular libraries on JVM machines. This book will help you build real-world NLP applications using a recipe-based approach. Prior knowledge of Natural Language Processing basics and Java programming is expected. |
| cloud natural language api: NATURAL LANGUAGE PROCESSING: UNLOCKING THE POWER OF TEXT AND SPEECH DATA Dr. Kirti Shukla, Ela Vashishtha, Dr. Mukta Sandhu, Pro. Ravi Choubey, 2023-05-23 The subject matter that is discussed in this book goes by a number of other names, including natural Words such as computational linguistics, human language technology, language processing, and language are all terms that are used in computational linguistics. computer voice and language processing. All of these titles refer to the same subject matter. This burgeoning academic subfield comprises a diverse array of scholarly subfields and is referred to by a variety of distinct names. This burgeoning area of study tries to allow computers to carry out valuable tasks utilizing human language. Examples of these activities include easing human-machine communication, enhancing human-to-human communication, or simply carrying out meaningful processing of text or voice input. The education of computers in the aforementioned activities is one of the key goals of this burgeoning discipline, which is still relatively new. A conversational agent is only one example of a job that is favorable in this category; nevertheless, this is just one of many possible examples. The HAL 900 computer, which was featured in Stanley Kubrick's film 2001: A Space Odyssey The protagonist of a film about a space journey is one of the most recognizable personalities to have come from the world of film in the 20th century. HAL is a man-made agent that is capable of complex language processing characteristics such as comprehending and speaking the English language. These skills were programmed into HAL by the people who developed the first Star Trek television series. At a pivotal point in the story, HAL even acquires the capacity to decipher what humans are saying by reading their lips. When he made his forecasts, we believe that HAL's creator, Arthur C. Clarke, was a little too excited about when an artificial agent such as HAL will be available to the general public. But where exactly did he make the mistake in his line of reasoning? What are the necessary steps that would need to be taken in order to build HAL, at the very least for the components that are associated with language? Conversational agents or dialogue systems are computer programs, like HAL, that are able to converse with people using natural language. Examples of such programs include Hal from the Star Trek franchise. These descriptors are assigned to the programs of their own accord. |
| cloud natural language api: Natural Language Processing in the Real World Jyotika Singh, 2023-07-03 Natural Language Processing in the Real World is a practical guide for applying data science and machine learning to build Natural Language Processing (NLP) solutions. Where traditional, academic-taught NLP is often accompanied by a data source or dataset to aid solution building, this book is situated in the real world where there may not be an existing rich dataset. This book covers the basic concepts behind NLP and text processing and discusses the applications across 15 industry verticals. From data sources and extraction to transformation and modelling, and classic Machine Learning to Deep Learning and Transformers, several popular applications of NLP are discussed and implemented. This book provides a hands-on and holistic guide for anyone looking to build NLP solutions, from students of Computer Science to those involved in large-scale industrial projects. |
| cloud natural language api: Official Google Cloud Certified Professional Data Engineer Study Guide Dan Sullivan, 2020-06-10 The proven Study Guide that prepares you for this new Google Cloud exam The Google Cloud Certified Professional Data Engineer Study Guide, provides everything you need to prepare for this important exam and master the skills necessary to land that coveted Google Cloud Professional Data Engineer certification. Beginning with a pre-book assessment quiz to evaluate what you know before you begin, each chapter features exam objectives and review questions, plus the online learning environment includes additional complete practice tests. Written by Dan Sullivan, a popular and experienced online course author for machine learning, big data, and Cloud topics, Google Cloud Certified Professional Data Engineer Study Guide is your ace in the hole for deploying and managing analytics and machine learning applications. Build and operationalize storage systems, pipelines, and compute infrastructure Understand machine learning models and learn how to select pre-built models Monitor and troubleshoot machine learning models Design analytics and machine learning applications that are secure, scalable, and highly available. This exam guide is designed to help you develop an in depth understanding of data engineering and machine learning on Google Cloud Platform. |
| cloud natural language api: The Self-Taught Cloud Computing Engineer Dr. Logan Song, 2023-09-22 Transform into a cloud-savvy professional by mastering cloud technologies through hands-on projects and expert guidance, paving the way for a thriving cloud computing career Key Features Learn all about cloud computing at your own pace with this easy-to-follow guide Develop a well-rounded skill set, encompassing fundamentals, data, machine learning, and security Work on real-world industrial projects and business use cases, and chart a path for your personal cloud career advancement Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionThe Self-Taught Cloud Computing Engineer is a comprehensive guide to mastering cloud computing concepts by building a broad and deep cloud knowledge base, developing hands-on cloud skills, and achieving professional cloud certifications. Even if you’re a beginner with a basic understanding of computer hardware and software, this book serves as the means to transition into a cloud computing career. Starting with the Amazon cloud, you’ll explore the fundamental AWS cloud services, then progress to advanced AWS cloud services in the domains of data, machine learning, and security. Next, you’ll build proficiency in Microsoft Azure Cloud and Google Cloud Platform (GCP) by examining the common attributes of the three clouds while distinguishing their unique features. You’ll further enhance your skills through practical experience on these platforms with real-life cloud project implementations. Finally, you’ll find expert guidance on cloud certifications and career development. By the end of this cloud computing book, you’ll have become a cloud-savvy professional well-versed in AWS, Azure, and GCP, ready to pursue cloud certifications to validate your skills.What you will learn Develop the core skills needed to work with cloud computing platforms such as AWS, Azure, and GCP Gain proficiency in compute, storage, and networking services across multi-cloud and hybrid-cloud environments Integrate cloud databases, big data, and machine learning services in multi-cloud environments Design and develop data pipelines, encompassing data ingestion, storage, processing, and visualization in the clouds Implement machine learning pipelines in a multi-cloud environment Secure cloud infrastructure ecosystems with advanced cloud security services Who this book is for Whether you're new to cloud computing or a seasoned professional looking to expand your expertise, this book is for anyone in the information technology domain who aspires to thrive in the realm of cloud computing. With this comprehensive roadmap, you’ll have the tools to build a successful cloud computing career. |
| cloud natural language api: Cloud-based Multi-Modal Information Analytics Srinidhi Hiriyannaiah, Siddesh G M, Srinivasa K G, 2023-06-29 Cloud based Multi-Modal Information Analytics: A Hands-on Approach discusses the various modalities of data and provide an aggregated solution using cloud. It includes the fundamentals of neural networks, different types and how they can be used for the multi-modal information analytics. The various application areas that are image-centric and videos are also presented with deployment solutions in the cloud. Features Life cycle of the multi- modal data analytics is discussed with applications of modalities of text, image, and video. Deep Learning fundamentals and architectures covering convolutional Neural Networks, recurrremt neural networks, and types of learning for different multi-modal networks. Applications of Multi-Modal Analytics covering Text , Speech, and Image. This book is aimed at researchers in Multi-modal analytics and related areas |
| cloud natural language api: Practical AI on the Google Cloud Platform Micheal Lanham, 2020-10-20 Working with AI is complicated and expensive for many developers. That's why cloud providers have stepped in to make it easier, offering free (or affordable) state-of-the-art models and training tools to get you started. With this book, you'll learn how to use Google's AI-powered cloud services to do everything from creating a chatbot to analyzing text, images, and video. Author Micheal Lanham demonstrates methods for building and training models step-by-step and shows you how to expand your models to accomplish increasingly complex tasks. If you have a good grasp of math and the Python language, you'll quickly get up to speed with Google Cloud Platform, whether you want to build an AI assistant or a simple business AI application. Learn key concepts for data science, machine learning, and deep learning Explore tools like Video AI and AutoML Tables Build a simple language processor using deep learning systems Perform image recognition using CNNs, transfer learning, and GANs Use Google's Dialogflow to create chatbots and conversational AI Analyze video with automatic video indexing, face detection, and TensorFlow Hub Build a complete working AI agent application |
| cloud natural language api: Linking Theory and Practice of Digital Libraries Gianmaria Silvello, Oscar Corcho, Paolo Manghi, Giorgio Maria Di Nunzio, Koraljka Golub, Nicola Ferro, Antonella Poggi, 2022-09-14 This book constitutes the proceedings of the 26th International Conference on Theory and Practice of Digital Libraries, TPDL 2022, which took place in Padua, Italy, in September 2022. The 18 full papers, 27 short papers and 15 accelerating innovation papers included in these proceedings were carefully reviewed and selected from 107 submissions. They focus on digital libraries and associated technical, practical, and social issues. |
| cloud natural language api: Democratizing RPA with Power Automate Desktop Peter Krause, 2023-04-28 Discover how desktop flows can interact with your everyday tools and automate tasks, freeing up time to do more important things Purchase of the print or Kindle book includes a free PDF eBook Key Features Learn how Office programs can assist with automating recurring tasks Maintain superior work quality by including daily desktop and web applications in your flows Enrich your flows with additional AI-based information and integrate them with cloud systems Book DescriptionWhether you want to organize simple files or perform more complex consolidations between different Office programs and remote-control applications that don't allow outside access, Power Automate Desktop helps meet these challenges. This book shows you how to leverage this workflow automation platform by explaining the underlying RPA concepts in a step-by-step way. You’ll start with simple flows that can be easily recorded and further processed using the built-in recorder. Later, you’ll learn how to use the more advanced actions to automate folder and file management and enable Office programs to interact with each other. You’ll also get to grips with integrating desktop flows into other cloud environments and further enhance their value using AI. As you progress, you’ll understand how flows can run unattended and how they are managed in the Power Platform, as well as key concepts such as creating, modifying, debugging, and error-handling UI flows. Finally, the book will guide you to use Process Automation Designer (PAD) in conjunction with your frequently used desktop systems to automate routine tasks. By the end of this book, you’ll have become a Power Automate Desktop expert, automating both professional and personal tasks.What you will learn Master RPA with Power Automate Desktop to commence your debut flow Grasp all essential product concepts such as UI flow creation and modification, debugging, and error handling Use PAD to automate tasks in conjunction with the frequently used systems on your desktop Attain proficiency in configuring flows that run unattended to achieve seamless automation Discover how to use AI to enrich your flows with insights from different AI models Explore how to integrate a flow in a broader cloud context Who this book is for Whether you’re a home user looking to automate simple tasks on your workstation or a business user or citizen developer seeking to automate more complex rule-based processes, this book will help you overcome the challenge. No knowledge of a programming language is required, but in the more advanced chapters, a general understanding of information technology, including basic programming language structures, protocols, and cloud concepts, will be helpful. |
| cloud natural language api: Google Machine Learning and Generative AI for Solutions Architects Kieran Kavanagh, 2024-06-28 Architect and run real-world AI/ML solutions at scale on Google Cloud, and discover best practices to address common industry challenges effectively Key Features Understand key concepts, from fundamentals through to complex topics, via a methodical approach Build real-world end-to-end MLOps solutions and generative AI applications on Google Cloud Get your hands on a code repository with over 20 hands-on projects for all stages of the ML model development lifecycle Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionMost companies today are incorporating AI/ML into their businesses. Building and running apps utilizing AI/ML effectively is tough. This book, authored by a principal architect with about two decades of industry experience, who has led cross-functional teams to design, plan, implement, and govern enterprise cloud strategies, shows you exactly how to design and run AI/ML workloads successfully using years of experience from some of the world’s leading tech companies. You’ll get a clear understanding of essential fundamental AI/ML concepts, before moving on to complex topics with the help of examples and hands-on activities. This will help you explore advanced, cutting-edge AI/ML applications that address real-world use cases in today’s market. You’ll recognize the common challenges that companies face when implementing AI/ML workloads, and discover industry-proven best practices to overcome these. The chapters also teach you about the vast AI/ML landscape on Google Cloud and how to implement all the steps needed in a typical AI/ML project. You’ll use services such as BigQuery to prepare data; Vertex AI to train, deploy, monitor, and scale models in production; as well as MLOps to automate the entire process. By the end of this book, you will be able to unlock the full potential of Google Cloud's AI/ML offerings.What you will learn Build solutions with open-source offerings on Google Cloud, such as TensorFlow, PyTorch, and Spark Source, understand, and prepare data for ML workloads Build, train, and deploy ML models on Google Cloud Create an effective MLOps strategy and implement MLOps workloads on Google Cloud Discover common challenges in typical AI/ML projects and get solutions from experts Explore vector databases and their importance in Generative AI applications Uncover new Gen AI patterns such as Retrieval Augmented Generation (RAG), agents, and agentic workflows Who this book is for This book is for aspiring solutions architects looking to design and implement AI/ML solutions on Google Cloud. Although this book is suitable for both beginners and experienced practitioners, basic knowledge of Python and ML concepts is required. The book focuses on how AI/ML is used in the real world on Google Cloud. It briefly covers the basics at the beginning to establish a baseline for you, but it does not go into depth on the underlying mathematical concepts that are readily available in academic material. |
| cloud natural language api: Enterprise AI in the Cloud Rabi Jay, 2023-12-20 Embrace emerging AI trends and integrate your operations with cutting-edge solutions Enterprise AI in the Cloud: A Practical Guide to Deploying End-to-End Machine Learning and ChatGPT Solutions is an indispensable resource for professionals and companies who want to bring new AI technologies like generative AI, ChatGPT, and machine learning (ML) into their suite of cloud-based solutions. If you want to set up AI platforms in the cloud quickly and confidently and drive your business forward with the power of AI, this book is the ultimate go-to guide. The author shows you how to start an enterprise-wide AI transformation effort, taking you all the way through to implementation, with clearly defined processes, numerous examples, and hands-on exercises. You’ll also discover best practices on optimizing cloud infrastructure for scalability and automation. Enterprise AI in the Cloud helps you gain a solid understanding of: AI-First Strategy: Adopt a comprehensive approach to implementing corporate AI systems in the cloud and at scale, using an AI-First strategy to drive innovation State-of-the-Art Use Cases: Learn from emerging AI/ML use cases, such as ChatGPT, VR/AR, blockchain, metaverse, hyper-automation, generative AI, transformer models, Keras, TensorFlow in the cloud, and quantum machine learning Platform Scalability and MLOps (ML Operations): Select the ideal cloud platform and adopt best practices on optimizing cloud infrastructure for scalability and automation AWS, Azure, Google ML: Understand the machine learning lifecycle, from framing problems to deploying models and beyond, leveraging the full power of Azure, AWS, and Google Cloud platforms AI-Driven Innovation Excellence: Get practical advice on identifying potential use cases, developing a winning AI strategy and portfolio, and driving an innovation culture Ethical and Trustworthy AI Mastery: Implement Responsible AI by avoiding common risks while maintaining transparency and ethics Scaling AI Enterprise-Wide: Scale your AI implementation using Strategic Change Management, AI Maturity Models, AI Center of Excellence, and AI Operating Model Whether you're a beginner or an experienced AI or MLOps engineer, business or technology leader, or an AI student or enthusiast, this comprehensive resource empowers you to confidently build and use AI models in production, bridging the gap between proof-of-concept projects and real-world AI deployments. With over 300 review questions, 50 hands-on exercises, templates, and hundreds of best practice tips to guide you through every step of the way, this book is a must-read for anyone seeking to accelerate AI transformation across their enterprise. |
| cloud natural language api: The Future of Finance Henri Arslanian, Fabrice Fischer, 2019-07-15 This book, written jointly by an engineer and artificial intelligence expert along with a lawyer and banker, is a glimpse on what the future of the financial services will look like and the impact it will have on society. The first half of the book provides a detailed yet easy to understand educational and technical overview of FinTech, artificial intelligence and cryptocurrencies including the existing industry pain points and the new technological enablers. The second half provides a practical, concise and engaging overview of their latest trends and their impact on the future of the financial services industry including numerous use cases and practical examples. The book is a must read for any professional currently working in finance, any student studying the topic or anyone curious on how the future of finance will look like. |
| cloud natural language api: Practical Data Science with SAP Greg Foss, Paul Modderman, 2019-09-18 Learn how to fuse today's data science tools and techniques with your SAP enterprise resource planning (ERP) system. With this practical guide, SAP veterans Greg Foss and Paul Modderman demonstrate how to use several data analysis tools to solve interesting problems with your SAP data. Data engineers and scientists will explore ways to add SAP data to their analysis processes, while SAP business analysts will learn practical methods for answering questions about the business. By focusing on grounded explanations of both SAP processes and data science tools, this book gives data scientists and business analysts powerful methods for discovering deep data truths. You'll explore: Examples of how data analysis can help you solve several SAP challenges Natural language processing for unlocking the secrets in text Data science techniques for data clustering and segmentation Methods for detecting anomalies in your SAP data Data visualization techniques for making your data come to life |
| cloud natural language api: Social, Cultural, and Behavioral Modeling Robert Thomson, |
| cloud natural language api: Proceedings of International Conference on Computational Intelligence Ritu Tiwari, Mario F. Pavone, Mukesh Saraswat, 2023-07-12 The book presents high quality research papers presented at International Conference on Computational Intelligence (ICCI 2022) held at Indian Institute of Information Technology Pune, India during 29 – 30 December, 2022. The topics covered are artificial intelligence, neural network, deep learning techniques, fuzzy theory and systems, rough sets, self-organizing maps, machine learning, chaotic systems, multi-agent systems, computational optimization ensemble classifiers, reinforcement learning, decision trees, support vector machines, hybrid learning, statistical learning, metaheuristics algorithms: evolutionary and swarm-based algorithms like genetic algorithms, genetic programming, differential evolution, particle swarm optimization, whale optimization, spider monkey optimization, firefly algorithm, memetic algorithms. And also machine vision, Internet of Things, image processing, image segmentation, data clustering, sentiment analysis, big data, computer networks, signal processing, supply chain management, web and text mining, distributed systems, bioinformatics, embedded systems, expert system, forecasting, pattern recognition, planning and scheduling, time series analysis, human-computer interaction, web mining, natural language processing, multimedia systems, and quantum computing. |
| cloud natural language api: PaaS Mastery: Platform As A Service Rob Botwright, 101-01-01 Are you ready to master the world of Platform as a Service (PaaS) and supercharge your cloud computing skills? Look no further than the PaaS Mastery book bundle – your all-in-one guide to Azure Pipelines, Google Cloud, Microsoft Azure, and IBM Cloud. 📘 Book 1: PaaS Mastery: Navigating Azure Pipelines and Beyond · Are you curious about Azure Pipelines and how it can revolutionize your application deployment processes? · This book provides hands-on guidance, best practices, and real-world examples to help you harness the power of Azure PaaS. · Whether you're a developer, IT professional, or decision-maker, you'll unlock the secrets to streamlining your application development and deployment. 📘 Book 2: Cloud Powerhouse: Mastering PaaS with Google, Azure, and IBM · Dive into the PaaS offerings of three cloud giants: Google Cloud, Microsoft Azure, and IBM Cloud. · Gain the knowledge to leverage their PaaS platforms effectively and discover how they redefine cloud computing. · This volume equips you with the skills to navigate the diverse cloud ecosystems of these powerhouses. 📘 Book 3: Platform as a Service Unleashed: A Comprehensive Guide · Delve deep into the unique features and capabilities of Google Cloud, Microsoft Azure, and IBM Cloud. · This book serves as a valuable reference guide, helping you make informed choices about the platform that aligns best with your organization's needs. · It's an essential resource for anyone looking to maximize the potential of PaaS. 📘 Book 4: From Novice to Pro: PaaS Mastery Across Clouds · Ready to go from a PaaS novice to a pro? This book is your ultimate guide. · Explore optimization strategies, learn how to combine multiple cloud platforms, and advance your skills in cloud computing. · Whether you're just starting or looking to enhance your expertise, this volume has you covered. 🚀 Why Choose PaaS Mastery? · Comprehensive Coverage: Master the ins and outs of PaaS across multiple cloud providers. · Hands-On Guidance: Benefit from real-world examples and practical advice. · Future-Proof Skills: Stay ahead in the dynamic world of cloud computing. · Valuable Reference: Access a treasure trove of knowledge to make informed decisions. · Perfect for All Levels: Whether you're a beginner or an expert, there's something for everyone. Don't miss this opportunity to become a PaaS expert. Get the PaaS Mastery book bundle today and elevate your cloud computing skills to new heights. Your journey to PaaS mastery begins here! |
| cloud natural language api: Google Cloud for Developers Hector Parra Martinez, Isaac Hernandez Vargas, 2023-05-26 Unlock your potential with this ultimate guide to Google Cloud – packed with expert tips, coding techniques, legacy migration, and application extension strategies Purchase of the print or Kindle book includes a free PDF eBook Key Features Maximize your code potential using Google Cloud services Migrate legacy code to the cloud seamlessly and create code that runs anywhere Use hands-on examples to learn and showcase your experience with Google Cloud Book Description As more organizations embrace cloud computing, developers new to the cloud often feel overwhelmed by cloud migration and code running directly on the cloud. Google Cloud for Developers comes packed with practical tips and expert advice to accelerate your application development journey and help you unlock the full potential of cloud computing. You'll begin by understanding and comparing all the available options to run your code. You'll write, deploy, monitor, and troubleshoot your code without leaving the Google Cloud IDE while selecting the best option – serverless or GKE containers – for each use case. After that, you'll get to grips with the basic Google Cloud infrastructure services and connect your code with public APIs. This will help you add features to your application, such as language translation and object detection in images or videos. Furthermore, you'll explore a comprehensive list of tips and best practices to make your migration smooth. You'll also gain the necessary knowledge to write code from scratch, by employing the basics of hybrid cloud applications and build services that can run virtually anywhere. By the end of this book, you'll be well equipped to carry out the application development process and successfully move your code to Google Cloud. What you will learn Understand how to write, run, and troubleshoot code on Google Cloud Choose between serverless or GKE containers for running your code Connect your code to Google Cloud services using public APIs Migrate your code to Google Cloud flawlessly Build hybrid cloud solutions that can run virtually anywhere Get to grips with Cloud Functions, App Engine, GKE, and Anthos Who this book is for Google Cloud for Developers is for cloud architects, engineers, or developers willing to migrate their applications and services to Google Cloud or build them from scratch. Entrepreneurs in early-stage start-ups and IT professionals who want to know more about Google Cloud from a developer perspective will also benefit from this book. A basic understanding of Cloud concepts and basic experience in writing Python and Shell scripts is a must. |
| cloud natural language api: The Definitive Guide to Google Vertex AI Jasmeet Bhatia, Kartik Chaudhary, 2023-12-29 Implement machine learning pipelines with Google Cloud Vertex AI Key Features Understand the role of an AI platform and MLOps practices in machine learning projects Get acquainted with Google Vertex AI tools and offerings that help accelerate the creation of end-to-end ML solutions Implement Vision, NLP, and recommendation-based real-world ML models on Google Cloud Platform Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionWhile AI has become an integral part of every organization today, the development of large-scale ML solutions and management of complex ML workflows in production continue to pose challenges for many. Google’s unified data and AI platform, Vertex AI, directly addresses these challenges with its array of MLOPs tools designed for overall workflow management. This book is a comprehensive guide that lets you explore Google Vertex AI’s easy-to-advanced level features for end-to-end ML solution development. Throughout this book, you’ll discover how Vertex AI empowers you by providing essential tools for critical tasks, including data management, model building, large-scale experimentations, metadata logging, model deployments, and monitoring. You’ll learn how to harness the full potential of Vertex AI for developing and deploying no-code, low-code, or fully customized ML solutions. This book takes a hands-on approach to developing u deploying some real-world ML solutions on Google Cloud, leveraging key technologies such as Vision, NLP, generative AI, and recommendation systems. Additionally, this book covers pre-built and turnkey solution offerings as well as guidance on seamlessly integrating them into your ML workflows. By the end of this book, you’ll have the confidence to develop and deploy large-scale production-grade ML solutions using the MLOps tooling and best practices from Google.What you will learn Understand the ML lifecycle, challenges, and importance of MLOps Get started with ML model development quickly using Google Vertex AI Manage datasets, artifacts, and experiments Develop no-code, low-code, and custom AI solution on Google Cloud Implement advanced model optimization techniques and tooling Understand pre-built and turnkey AI solution offerings from Google Build and deploy custom ML models for real-world applications Explore the latest generative AI tools within Vertex AI Who this book is for If you are a machine learning practitioner who wants to learn end-to-end ML solution development on Google Cloud Platform using MLOps best practices and tools offered by Google Vertex AI, this is the book for you. |
| cloud natural language api: Data Intensive Computing Applications for Big Data M. Mittal, V.E. Balas, D.J. Hemanth, 2018-01-31 The book ‘Data Intensive Computing Applications for Big Data’ discusses the technical concepts of big data, data intensive computing through machine learning, soft computing and parallel computing paradigms. It brings together researchers to report their latest results or progress in the development of the above mentioned areas. Since there are few books on this specific subject, the editors aim to provide a common platform for researchers working in this area to exhibit their novel findings. The book is intended as a reference work for advanced undergraduates and graduate students, as well as multidisciplinary, interdisciplinary and transdisciplinary research workers and scientists on the subjects of big data and cloud/parallel and distributed computing, and explains didactically many of the core concepts of these approaches for practical applications. It is organized into 24 chapters providing a comprehensive overview of big data analysis using parallel computing and addresses the complete data science workflow in the cloud, as well as dealing with privacy issues and the challenges faced in a data-intensive cloud computing environment. The book explores both fundamental and high-level concepts, and will serve as a manual for those in the industry, while also helping beginners to understand the basic and advanced aspects of big data and cloud computing. |
| cloud natural language api: Google Cloud Professional Data Engineer Exam Practice Questions and Dumps Zoom Books, A Professional Data Engineer authorize data-driven decision making by collecting, transforming, and publishing data. A Data Engineer should be able to blueprint, build, operationalize, secure, and monitor data processing systems with a particular emphasis on security and compliance; scalability and efficiency; reliability and fidelity; and flexibility and portability. A Data Engineer should also be able to leverage, deploy, and continuous train pre-existing machine learning models. Here we’ve brought best Exam practice questions for Google Cloud so that you can prepare well for Professional Data Engineer exam. Unlike other online simulation practice tests, you get an eBook version that is easy to read & remember these questions. You can simply rely on these questions for successfully certifying this exam. |
| cloud natural language api: Big Data, Cloud Computing, Data Science & Engineering Roger Lee, 2018-08-13 This book presents the outcomes of the 3rd IEEE/ACIS International Conference on Big Data, Cloud Computing, Data Science & Engineering (BCD 2018), which was held on July 10–12, 2018 in Kanazawa. The aim of the conference was to bring together researchers and scientists, businesspeople and entrepreneurs, teachers, engineers, computer users, and students to discuss the various fields of computer science, to share their experiences, and to exchange new ideas and information in a meaningful way. All aspects (theory, applications and tools) of computer and information science, the practical challenges encountered along the way, and the solutions adopted to solve them are all explored here. The conference organizers selected the best papers from among those accepted for presentation. The papers were chosen on the basis of review scores submitted by members of the program committee and subsequently underwent further rigorous review. Following this second round of review, 13 of the conference’s most promising papers were selected for this Springer (SCI) book. We eagerly await the important contributions that we know these authors will make to the field of computer and information science. |
| cloud natural language api: GOOGLE CLOUD PLATFORM FOR ENTERPRISE MLOPS:A PRACTICAL GUIDE TO CLOUD COMPUTING: PART ONE Jothi Periasamy, 2022-12-12 |
| cloud natural language api: Deep Learning Models on Cloud Platforms Vijay Ramamoorthi, 2024-07-25 Deep Learning Models on Cloud Platforms provides an in-depth exploration of the integration of deep learning techniques with cloud computing environments. Architectures, and frameworks for developing and deploying deep learning models at scale. It addresses practical considerations, including data management, computational resources, and cost-efficiency, while highlighting popular cloud platforms like AWS, Google Cloud, and Azure. Through real-world examples and case studies, readers will gain insights into best practices for leveraging cloud infrastructure to enhance deep learning capabilities and drive innovation across various industries. |
| cloud natural language api: Handbook of Cloud Computing Dr. Anand Nayyar, 2019-09-18 Great POSSIBILITIES and high future prospects to become ten times folds in the near FUTURE DESCRIPTION The book ÒHandbook of Cloud ComputingÓ provides the latest and in-depth information of this relatively new and another platform for scientific computing which has great possibilities and high future prospects to become ten folds in near future. The book covers in comprehensive manner all aspects and terminologies associated with cloud computing like SaaS, PaaS and IaaS and also elaborates almost every cloud computing service model. The book highlights several other aspects of cloud computing like Security, Resource allocation, Simulation Platforms and futuristic trend i.e. Mobile cloud computing. The book will benefit all the readers with all in-depth technical information which is required to understand current and futuristic concepts of cloud computing. No prior knowledge of cloud computing or any of its related technology is required in reading this book. KEY FEATURES Comprehensively gives clear picture of current state-of-the-art aspect of cloud computing by elaboratingÊ terminologies, models and other related terms. Enlightens all major players in Cloud Computing industry providing services in terms of SaaS, PaaS and IaaS. Highlights Cloud Computing Simulators, Security Aspect and Resource Allocation. In-depth presentation with well-illustrated diagrams and simple to understand technical concepts of cloud. WHAT WILL YOU LEARN Cloud Computing, Virtualisation Software as a Service, Platform as a Service, Infrastructure as a Service Data in Cloud and its SecurityÊ Cloud Computing Ð Simulation, Mobile Cloud Computing Specific Cloud Service Models Resource Allocation in Cloud Computing WHO THIS BOOK IS FOR Students of Polytechnic Diploma Classes- Computer Science/ Information Technology Graduate Students- Computer Science/ CSE / IT/ Computer Applications Master Class StudentsÑMsc (CS/IT)/ MCA/ M.Phil, M.Tech, M.S. ResearcherÕsÑPh.D Research Scholars doing work in Virtualization, Cloud Computing and Cloud Security Industry Professionals- Preparing for Certifications, Implementing Cloud Computing and even working on Cloud Security Table of Contents 1. Ê Ê Introduction to Cloud Computing 2. Ê Ê Virtualisation 3. Ê Ê Software as a Service 4. Ê Ê Platform as a Service 5. Ê Ê Infrastructure as a Service 6. Ê Ê Data in Cloud 7. Ê Ê Cloud SecurityÊ 8. Ê Ê Cloud Computing Ð Simulation 9. Ê Ê Specific Cloud Service Models 10. Ê Resource Allocation in Cloud Computing 11. Ê Mobile Cloud Computing |
| cloud natural language api: Intelligent Computing, Information and Control Systems A. Pasumpon Pandian, Klimis Ntalianis, Ram Palanisamy, 2019-10-18 From past decades, Computational intelligence embraces a number of nature-inspired computational techniques which mainly encompasses fuzzy sets, genetic algorithms, artificial neural networks and hybrid neuro-fuzzy systems to address the computational complexities such as uncertainties, vagueness and stochastic nature of various computational problems practically. At the same time, Intelligent Control systems are emerging as an innovative methodology which is inspired by various computational intelligence process to promote a control over the systems without the use of any mathematical models. To address the effective use of intelligent control in Computational intelligence systems, International Conference on Intelligent Computing, Information and Control Systems (ICICCS 2019) is initiated to encompass the various research works that helps to develop and advance the next-generation intelligent computing and control systems. This book integrates the computational intelligence and intelligent control systems to provide a powerful methodology for a wide range of data analytics issues in industries and societal applications. The recent research advances in computational intelligence and control systems are addressed, which provide very promising results in various industry, business and societal studies. This book also presents the new algorithms and methodologies for promoting advances in common intelligent computing and control methodologies including evolutionary computation, artificial life, virtual infrastructures, fuzzy logic, artificial immune systems, neural networks and various neuro-hybrid methodologies. This book will be pragmatic for researchers, academicians and students dealing with mathematically intransigent problems. It is intended for both academicians and researchers in the field of Intelligent Computing, Information and Control Systems, along with the distinctive readers in the fields of computational and artificial intelligence to gain more knowledge on Intelligent computing and control systems and their real-world applications. |
| cloud natural language api: Data-Driven Modelling and Predictive Analytics in Business and Finance Alex Khang, Rashmi Gujrati, Hayri Uygun, R. K. Tailor, Sanjaya Gaur, 2024-07-24 Data-driven and AI-aided applications are next-generation technologies that can be used to visualize and realize intelligent transactions in finance, banking, and business. These transactions will be enabled by powerful data-driven solutions, IoT technologies, AI-aided techniques, data analytics, and visualization tools. To implement these solutions, frameworks will be needed to support human control of intelligent computing and modern business systems. The power and consistency of data-driven competencies are a critical challenge, and so is developing explainable AI (XAI) to make data-driven transactions transparent. Data- Driven Modelling and Predictive Analytics in Business and Finance covers the need for intelligent business solutions and applications. Explaining how business applications use algorithms and models to bring out the desired results, the book covers: Data-driven modelling Predictive analytics Data analytics and visualization tools AI-aided applications Cybersecurity techniques Cloud computing IoT-enabled systems for developing smart financial systems This book was written for business analysts, financial analysts, scholars, researchers, academics, professionals, and students so they may be able to share and contribute new ideas, methodologies, technologies, approaches, models, frameworks, theories, and practices. |
| cloud natural language api: Google Cloud Platform for Data Engineering Alasdair Gilchrist, Google Cloud Platform for Data Engineering is designed to take the beginner through a journey to become a competent and certified GCP data engineer. The book, therefore, is split into three parts; the first part covers fundamental concepts of data engineering and data analysis from a platform and technology-neutral perspective. Reading part 1 will bring a beginner up to speed with the generic concepts, terms and technologies we use in data engineering. The second part, which is a high-level but comprehensive introduction to all the concepts, components, tools and services available to us within the Google Cloud Platform. Completing this section will provide the beginner to GCP and data engineering with a solid foundation on the architecture and capabilities of the GCP. Part 3, however, is where we delve into the moderate to advanced techniques that data engineers need to know and be able to carry out. By this time the raw beginner you started the journey at the beginning of part 1 will be a knowledgable albeit inexperienced data engineer. However, by the conclusion of part 3, they will have gained the advanced knowledge of data engineering techniques and practices on the GCP to pass not only the certification exam but also most interviews and practical tests with confidence. In short part 3, will provide the prospective data engineer with detailed knowledge on setting up and configuring DataProc - GCPs version of the Spark/Hadoop ecosystem for big data. They will also learn how to build and test streaming and batch data pipelines using pub/sub/ dataFlow and BigQuery. Furthermore, they will learn how to integrate all the ML and AI Platform components and APIs. They will be accomplished in connecting data analysis and visualisation tools such as Datalab, DataStudio and AI notebooks amongst others. They will also by now know how to build and train a TensorFlow DNN using APIs and Keras and optimise it to run large public data sets. Also, they will know how to provision and use Kubeflow and Kube Pipelines within Google Kubernetes engines to run container workloads as well as how to take advantage of serverless technologies such as Cloud Run and Cloud Functions to build transparent and seamless data processing platforms. The best part of the book though is its compartmental design which means that anyone from a beginner to an intermediate can join the book at whatever point they feel comfortable. |
| cloud natural language api: Google Certification Guide -Google Professional Cloud Architect Cybellium Ltd, Google Certification Guide - Google Professional Cloud Architect Architect Your Success in the Google Cloud Elevate your cloud architecture skills with this essential guide to becoming a Google Professional Cloud Architect. This comprehensive book is your ally in mastering the complex landscape of Google Cloud architecture, providing you with the knowledge and confidence needed to excel in the certification exam and in your professional career. Inside, You'll Find: Advanced Architectural Insights: Delve into the intricacies of designing and managing robust, secure, and efficient solutions on Google Cloud. Real-World Scenarios: Understand the practical applications of Google Cloud services through detailed case studies and hands-on examples, demonstrating architecture in action. Exam-Focused Approach: Get a thorough breakdown of the exam format, key topics, and strategies, along with practice questions designed to mirror the real exam experience. Latest Cloud Innovations: Stay ahead of the curve with insights into the newest features and trends in Google Cloud, ensuring your knowledge remains cutting-edge. Written by a Cloud Architecture Expert Authored by an experienced cloud architect specializing in Google Cloud, this guide combines deep technical expertise with practical insights, offering a rich and comprehensive learning experience. Your Roadmap to Professional Certification Whether you are an experienced cloud architect or looking to take your skills to the next level, this book is your comprehensive companion, guiding you through the complexities of Google Cloud architecture and preparing you for the Professional Cloud Architect exam. Advance Your Cloud Architecture Career This guide goes beyond exam preparation; it's a deep dive into the art and science of cloud architecture in the Google Cloud environment, designed to equip you with the skills and knowledge needed to excel as a professional cloud architect. Begin Your Architectural Mastery Take the first step towards becoming a certified Google Professional Cloud Architect. With this guide, you're not just preparing for an exam; you're preparing to become a leader in the transformative world of cloud architecture. © 2023 Cybellium Ltd. All rights reserved. www.cybellium.com |
| cloud natural language api: Official Google Cloud Certified Professional Machine Learning Engineer Study Guide Mona Mona, Pratap Ramamurthy, 2023-10-27 Expert, guidance for the Google Cloud Machine Learning certification exam In Google Cloud Certified Professional Machine Learning Study Guide, a team of accomplished artificial intelligence (AI) and machine learning (ML) specialists delivers an expert roadmap to AI and ML on the Google Cloud Platform based on new exam curriculum. With Sybex, you’ll prepare faster and smarter for the Google Cloud Certified Professional Machine Learning Engineer exam and get ready to hit the ground running on your first day at your new job as an ML engineer. The book walks readers through the machine learning process from start to finish, starting with data, feature engineering, model training, and deployment on Google Cloud. It also discusses best practices on when to pick a custom model vs AutoML or pretrained models with Vertex AI platform. All technologies such as Tensorflow, Kubeflow, and Vertex AI are presented by way of real-world scenarios to help you apply the theory to practical examples and show you how IT professionals design, build, and operate secure ML cloud environments. The book also shows you how to: Frame ML problems and architect ML solutions from scratch Banish test anxiety by verifying and checking your progress with built-in self-assessments and other practical tools Use the Sybex online practice environment, complete with practice questions and explanations, a glossary, objective maps, and flash cards A can’t-miss resource for everyone preparing for the Google Cloud Certified Professional Machine Learning certification exam, or for a new career in ML powered by the Google Cloud Platform, this Sybex Study Guide has everything you need to take the next step in your career. |
| cloud natural language api: Transformers for Natural Language Processing and Computer Vision Denis Rothman, 2024-02-29 The definitive guide to LLMs, from architectures, pretraining, and fine-tuning to Retrieval Augmented Generation (RAG), multimodal Generative AI, risks, and implementations with ChatGPT Plus with GPT-4, Hugging Face, and Vertex AI Key Features Compare and contrast 20+ models (including GPT-4, BERT, and Llama 2) and multiple platforms and libraries to find the right solution for your project Apply RAG with LLMs using customized texts and embeddings Mitigate LLM risks, such as hallucinations, using moderation models and knowledge bases Purchase of the print or Kindle book includes a free eBook in PDF format Book DescriptionTransformers for Natural Language Processing and Computer Vision, Third Edition, explores Large Language Model (LLM) architectures, applications, and various platforms (Hugging Face, OpenAI, and Google Vertex AI) used for Natural Language Processing (NLP) and Computer Vision (CV). The book guides you through different transformer architectures to the latest Foundation Models and Generative AI. You’ll pretrain and fine-tune LLMs and work through different use cases, from summarization to implementing question-answering systems with embedding-based search techniques. You will also learn the risks of LLMs, from hallucinations and memorization to privacy, and how to mitigate such risks using moderation models with rule and knowledge bases. You’ll implement Retrieval Augmented Generation (RAG) with LLMs to improve the accuracy of your models and gain greater control over LLM outputs. Dive into generative vision transformers and multimodal model architectures and build applications, such as image and video-to-text classifiers. Go further by combining different models and platforms and learning about AI agent replication. This book provides you with an understanding of transformer architectures, pretraining, fine-tuning, LLM use cases, and best practices.What you will learn Breakdown and understand the architectures of the Original Transformer, BERT, GPT models, T5, PaLM, ViT, CLIP, and DALL-E Fine-tune BERT, GPT, and PaLM 2 models Learn about different tokenizers and the best practices for preprocessing language data Pretrain a RoBERTa model from scratch Implement retrieval augmented generation and rules bases to mitigate hallucinations Visualize transformer model activity for deeper insights using BertViz, LIME, and SHAP Go in-depth into vision transformers with CLIP, DALL-E 2, DALL-E 3, and GPT-4V Who this book is for This book is ideal for NLP and CV engineers, software developers, data scientists, machine learning engineers, and technical leaders looking to advance their LLMs and generative AI skills or explore the latest trends in the field. Knowledge of Python and machine learning concepts is required to fully understand the use cases and code examples. However, with examples using LLM user interfaces, prompt engineering, and no-code model building, this book is great for anyone curious about the AI revolution. |
| cloud natural language api: Managing the Smart Revolution in Tourism Firms Francisco J. Navarro-Meneses, 2023-03-31 Smart technologies are revolutionizing tourism, as they are having a profound impact on the way tourists behave and on how firms interact with them and create value. The increasing availability of real-time Big Data and the advances made in data analytics techniques, artificial intelligence, and IoT, has begun to transform tourism organizations in ways not previously considered, and in a lasting manner. This book delivers the latest and most relevant advances in the field of smart transformation and the management practices that can be put into practice to continue creating value in the years to come. Divided into four main parts and 23 chapters, it highlights the challenges that the Smart Revolution brings to tourism firms by providing updated knowledge on the literature, research, and experiences of the author. The book will also provide a guide for action to business leaders and those approaching the fundamentals of the Smart Revolution for the first time. It will also serve as a valuable text for undergraduate and graduate students on specialized courses in tourism, technology, and business transformation. |
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Cloud Computing Services | Google Cloud
Meet your business challenges head on with cloud computing services from Google, including data management, hybrid & multi-cloud, and AI & ML.
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Cloud Storage | Google Cloud
Google Cloud Platform
Google Cloud Platform lets you build, deploy, and scale applications, websites, and services on the same infrastructure as Google.
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Meistern Sie geschäftliche Herausforderungen mit Cloud-Computing-Diensten von Google wie Datenverwaltung, Hybrid- und Multi-Cloud sowie KI und ML.
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Google Cloud offers a range of cloud computing services, including data management, AI, and hybrid cloud solutions.
云计算服务 | Google Cloud
借助 Google 的云计算服务，包括数据管理、混合云、多云以及 AI 和机器学习方面的服务，着力应对业务挑战。
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