| business rule engine python: AI and Business Rule Engines for Excel Power Users Paul Browne, Alex Porcelli, 2023-03-31 A power-packed manual to enhance your decision-making with the application of Business Rules using KIE, Drools, Kogito, MS Excel, Power Automate, Office Script, and MS Forms Purchase of the print or Kindle book includes a free PDF eBook Key FeaturesExplore the business rule tools by implementing real-world examples to write sophisticated rulesDiscover how decision services solve current business challenges using AICombine rules with workflows and scripting to deploy a cloud-based production environmentBook Description Microsoft Excel is widely adopted across diverse industries, but Excel Power Users often encounter limitations such as complex formulas, obscure business knowledge, and errors from using outdated sheets. They need a better enterprise-level solution, and this book introduces Business rules combined with the power of AI to tackle the limitations of Excel. This guide will give you a roadmap to link KIE (an industry-standard open-source application) to Microsoft's business process automation tools, such as Power Automate, Power Query, Office Script, Forms, VBA, Script Lab, and GitHub. You'll dive into the graphical Decision Modeling standard including decision tables, FEEL expressions, and advanced business rule editing and testing. By the end of the book, you'll be able to share your business knowledge as graphical models, deploy and execute these models in the cloud (with Azure and OpenShift), link them back to Excel, and then execute them as an end-to-end solution removing human intervention. You'll be equipped to solve your Excel queries and start using the next generation of Microsoft Office tools. What you will learnUse KIE and Drools decision services to write AI-based business rulesLink Business Rules to Excel using Power Query, Script Lab, Office Script, and VBABuild an end-to-end workflow with Microsoft Power Automate and Forms while integrating it with Excel and KogitoCollaborate on and deploy your decision models using OpenShift, Azure, and GitHubDiscover advanced editing using the graphical Decision Model Notation (DMN) and testing toolsUse Kogito to combine AI solutions with ExcelWho this book is for This book is for Excel power users, business users, and business analysts looking for a tool to capture their knowledge and deploy it as part of enterprise-grade systems. Working proficiency with MS Excel is required. Basic knowledge of web technologies and scripting would be an added advantage. |
| business rule engine python: Python Web Programming Steve Holden, David M. Beazley, 2002 A Python community leader teaches professionals how to integrate web applications with Python. |
| business rule engine python: arc42 by Example Dr. Gernot Starke, Michael Simons, Stefan Zörner, Ralf D. Müller, 2019-10-07 Document the architecture of your software easily with this highly practical, open-source template. Key FeaturesGet to grips with leveraging the features of arc42 to create insightful documentsLearn the concepts of software architecture documentation through real-world examplesDiscover techniques to create compact, helpful, and easy-to-read documentationBook Description When developers document the architecture of their systems, they often invent their own specific ways of articulating structures, designs, concepts, and decisions. What they need is a template that enables simple and efficient software architecture documentation. arc42 by Example shows how it's done through several real-world examples. Each example in the book, whether it is a chess engine, a huge CRM system, or a cool web system, starts with a brief description of the problem domain and the quality requirements. Then, you'll discover the system context with all the external interfaces. You'll dive into an overview of the solution strategy to implement the building blocks and runtime scenarios. The later chapters also explain various cross-cutting concerns and how they affect other aspects of a program. What you will learnUtilize arc42 to document a system's physical infrastructureLearn how to identify a system's scope and boundariesBreak a system down into building blocks and illustrate the relationships between themDiscover how to describe the runtime behavior of a systemKnow how to document design decisions and their reasonsExplore the risks and technical debt of your systemWho this book is for This book is for software developers and solutions architects who are looking for an easy, open-source tool to document their systems. It is a useful reference for those who are already using arc42. If you are new to arc42, this book is a great learning resource. For those of you who want to write better technical documentation will benefit from the general concepts covered in this book. |
| business rule engine python: New Trends in Software Methodologies, Tools and Techniques Hamido Fujita, Roberto Revetria, 2012 Software is the essential enabling means for science and the new economy. It helps us to create a more reliable, flexible and robust society. But software often falls short of our expectations. Current methodologies, tools, and techniques remain expensive and are not yet sufficiently reliable, while many promising approaches have proved to be no more than case-by-case oriented methods. This book contains extensively reviewed papers from the eleventh International Conference on New Trends in software Methodology, Tools and Techniques (SoMeT_12), held in Genoa, Italy, in September 2012. The conference provides an opportunity for scholars from the international research community to discuss and share research experiences of new software methodologies and techniques, and the contributions presented here address issues ranging from research practices and techniques and methodologies to proposing and reporting solutions for global world business. The emphasis has been on human-centric software methodologies, end-user development techniques and emotional reasoning, for an optimally harmonized performance between the design tool and the user.Topics covered include the handling of cognitive issues in software development to adapt it to the user's mental state and intelligent software design in software utilizing new aspects on conceptual ontology and semantics reflected on knowledge base system models. This book provides an opportunity for the software science community to show where we are today and where the future may take us. |
| business rule engine python: Modeling with Rules Using Semantic Knowledge Engineering Grzegorz J. Nalepa, 2017-10-04 This book proposes a consistent methodology for building intelligent systems. It puts forward several formal models for designing and implementing rules-based systems, and presents illustrative case studies of their applications. These include software engineering, business process systems, Semantic Web, and context-aware systems on mobile devices. Rules offer an intuitive yet powerful method for representing human knowledge, and intelligent systems based on rules have many important applications. However, their practical development requires proper techniques and models - a gap that this book effectively addresses. |
| business rule engine python: Machine Learning with Business Rules on IBM Z: Acting on Your Insights Mike Johnson, Chris Backhouse, Stéphane Faure, David Griffiths, Yann Kindelberger, Ke Wei Wei, Hao Zhang, IBM Redbooks, 2019-12-11 This Redpaper introduces the integration between two IBM products that you might like to consider when implementing a modern agile solution on your Z systems. The document briefly introduces Operational Decision Manager on z/OS and Machine learning on z/OS. In the case of Machine Learning we focus on the aspect of real-time scoring models and how these can be used with Business Rules to give better decisions. Note: Important changes since this document was written: This document was written for an older release of Operational Decision Manager for z/OS (ODM for z/OS). ODM for z/OS 8.9.1 required the writing of custom Java code to access a Watson Machine Learning for z/OS Scoring Service (this can be seen in ). Since that time ODM for z/OS version 8.10.1 has been released and much improves the integration experience. Integrating the two products no longer requires custom Java code. Using ODM for z/OS 8.10.1 or later you can use an automated wizard in the ODM tooling to: Browse and select a model from Watson Machine Learning Import the Machine Learning data model into your rule project Automatically generate a template rule that integrates a call to the Watson Machine Learning scoring service Download and read this document for: Individual introductions to ODM for z/OS and Machine learning Discussions on the benefits of using the two technologies together Information on integrating if you have not yet updated to ODM for z/OS 8.10.1 For information about the machine learning integration in ODM for z/OS 8.10.1 see IBM Watson Machine Learning for z/OS integration topic in the ODM for z/OS 8.10.x Knowledge Center |
| business rule engine python: Software Services for e-Business and e-Society Claude Godart, Norbert Gronau, Sushil Sharma, Gérôme Canals, 2009-09-09 I3E 2009 was held in Nancy, France, during September 23–25, hosted by Nancy University and INRIA Grand-Est at LORIA. The conference provided scientists andpractitionersofacademia,industryandgovernmentwithaforumwherethey presented their latest ?ndings concerning application of e-business, e-services and e-society, and the underlying technology to support these applications. The 9th IFIP Conference on e-Business, e-Services and e-Society, sponsored by IFIP WG 6.1. of Technical Committees TC6 in cooperation with TC11, and TC8 represents the continuation of previous events held in Zurich (Switzerland) in 2001, Lisbon (Portugal) in 2002, Sao Paulo (Brazil) in 2003, Toulouse (France) in 2004, Poznan (Poland) in 2005, Turku (Finland) in 2006, Wuhan (China) in 2007 and Tokyo (Japan) in 2008. The call for papers attracted papers from 31 countries from the ?ve con- nents. As a result, the I3E 2009 programo?ered 12 sessions of full-paper pres- tations. The 31 selected papers cover a wide and important variety of issues in e-Business,e-servicesande-society,including security,trust,andprivacy,ethical and societal issues, business organization, provision of services as software and software as services, and others. Extended versions of selected papers submitted to I3E 2009 will be published in the International Journal of e-Adoption and in AIS Transactions on Enterprise Systems. In addition, a 500-euros prize was awarded to the authors of the best paper selected by the Program Comm- tee. We thank all authors who submitted their papers, the Program Committee members and external reviewers for their excellent work. |
| business rule engine python: Object-Oriented Analysis and Design for Information Systems Raul Sidnei Wazlawick, 2024-03-16 Object-Oriented Analysis and Design for Information Systems, Second Edition clearly explains real object-oriented programming in practice. Expert author Raul Sidnei Wazlawick explains concepts such as object responsibility, visibility, and the real need for delegation in detail. The object-oriented code generated by using these concepts in a systematic way is concise, organized and reusable.The patterns and solutions presented in this book are based in research and industrial applications. You will come away with clarity regarding processes and use cases and a clear understanding of how to expand a use case. Wazlawick clearly explains how to build meaningful sequence diagrams. Object-Oriented Analysis and Design for Information Systems illustrates how and why building a class model is not just placing classes into a diagram. You will learn the necessary organizational patterns so that your software architecture will be maintainable. The Second Edition includes all new content shifting the focus of the book to agile software development, including Scrum software project management, BPMN diagrams, user stories, and Python code examples. - Provides updates on how to build better class models, which are more maintainable and understandable - Explains how to write use cases in a more efficient and standardized way, using more effective and less complex diagrams - Updates on how to build true object-oriented code with division of responsibility and delegation - Covers contemporary themes such as agile methodologies and BPMN (Business Process Modeling and Notation) |
| business rule engine python: Business Modeling and Software Design Boris Shishkov, 2022-07-30 This book constitutes the refereed proceedings of the 12h International Symposium on Business Modeling and Software Design, BMSD 2022, which took place in Fribourg, Switzerland, in June 2022. The 12 full and 9 short papers included in this book were carefully reviewed and selected from a total of 56 submissions. BMSD is a leading international forum that brings together researchers and practitioners interested in business modeling and its relation to software design. Particular areas of interest are: Business Processes and Enterprise Engineering; Business Models and Requirements; Business Models and Services; Business Models and Software; Information Systems Architectures and Paradigms; Data Aspects in Business Modeling and Software Development; Blockchain-Based Business Models and Information Systems; IoT and Implications for Enterprise Information Systems. Each year, a special theme is chosen, for making presentations and discussions more focused. The BMSD 2022 theme is: Information Systems Engineering and Trust. |
| business rule engine python: Metaprogramming in .NET Jason Bock, Kevin Hazzard, 2012-12-30 Summary Metaprogramming in .NET is designed to help readers understand the basic concepts, advantages, and potential pitfalls of metaprogramming. It introduces core concepts in clear, easy-to-follow language and then it takes you on a deep dive into the tools and techniques you'll use to implement them in your .NET code. You'll explore plenty of real-world examples that reinforce key concepts. When you finish, you'll be able to build high-performance, metaprogramming-enabled software with confidence. About the Technology When you write programs that create or modify other programs, you are metaprogramming. In .NET, you can use reflection as well as newer concepts like code generation and scriptable software. The emerging Roslyn project exposes the .NET compiler as an interactive API, allowing compile-time code analysis and just-in-time refactoring. About this Book Metaprogramming in .NET is a practical introduction to the use of metaprogramming to improve the performance and maintainability of your code. This book avoids abstract theory and instead teaches you solid practices you'll find useful immediately. It introduces core concepts like code generation and application composition in clear, easy-to-follow language. Written for readers comfortable with C# and the .NET framework—no prior experience with metaprogramming is required. Purchase of the print book comes with an offer of a free PDF, ePub, and Kindle eBook from Manning. Also available is all code from the book. What's Inside Metaprogramming concepts in plain language Creating scriptable software Code generation techniques The Dynamic Language Runtime About the Authors Kevin Hazzard is a Microsoft MVP, consultant, teacher, and developer community leader in the mid-Atlantic USA. Jason Bock is an author, Microsoft MVP, and the leader of the Twin Cities Code Camp. An excellent way to start fully using the power of metaprogramming.—From the Foreword by Rockford Lhotka, Creator of the CSLA .NET Framework Table of Contents PART 1 DEMYSTIFYING METAPROGRAMMING Metaprogramming concepts Exploring code and metadata with reflection PART 2 TECHNIQUES FOR GENERATING CODE The Text Template Transformation Toolkit (T4) Generating code with the CodeDOM Generating code with Reflection.Emit Generating code with expressions Generating code with IL rewriting PART 3 LANGUAGES AND TOOLS The Dynamic Language Runtime Languages and tools Managing the .NET Compiler |
| business rule engine python: Supervised Machine Learning with Python Taylor Smith, 2019-05-27 Teach your machine to think for itself! Key FeaturesDelve into supervised learning and grasp how a machine learns from dataImplement popular machine learning algorithms from scratch, developing a deep understanding along the wayExplore some of the most popular scientific and mathematical libraries in the Python languageBook Description Supervised machine learning is used in a wide range of sectors (such as finance, online advertising, and analytics) because it allows you to train your system to make pricing predictions, campaign adjustments, customer recommendations, and much more while the system self-adjusts and makes decisions on its own. As a result, it's crucial to know how a machine “learns” under the hood. This book will guide you through the implementation and nuances of many popular supervised machine learning algorithms while facilitating a deep understanding along the way. You’ll embark on this journey with a quick overview and see how supervised machine learning differs from unsupervised learning. Next, we explore parametric models such as linear and logistic regression, non-parametric methods such as decision trees, and various clustering techniques to facilitate decision-making and predictions. As we proceed, you'll work hands-on with recommender systems, which are widely used by online companies to increase user interaction and enrich shopping potential. Finally, you’ll wrap up with a brief foray into neural networks and transfer learning. By the end of this book, you’ll be equipped with hands-on techniques and will have gained the practical know-how you need to quickly and powerfully apply algorithms to new problems. What you will learnCrack how a machine learns a concept and generalize its understanding to new dataUncover the fundamental differences between parametric and non-parametric modelsImplement and grok several well-known supervised learning algorithms from scratchWork with models in domains such as ecommerce and marketingExpand your expertise and use various algorithms such as regression, decision trees, and clusteringBuild your own models capable of making predictionsDelve into the most popular approaches in deep learning such as transfer learning and neural networksWho this book is for This book is for aspiring machine learning developers who want to get started with supervised learning. Intermediate knowledge of Python programming—and some fundamental knowledge of supervised learning—are expected. |
| business rule engine python: Streaming Architecture Ted Dunning, Ellen Friedman, 2016-05-10 More and more data-driven companies are looking to adopt stream processing and streaming analytics. With this concise ebook, you’ll learn best practices for designing a reliable architecture that supports this emerging big-data paradigm. Authors Ted Dunning and Ellen Friedman (Real World Hadoop) help you explore some of the best technologies to handle stream processing and analytics, with a focus on the upstream queuing or message-passing layer. To illustrate the effectiveness of these technologies, this book also includes specific use cases. Ideal for developers and non-technical people alike, this book describes: Key elements in good design for streaming analytics, focusing on the essential characteristics of the messaging layer New messaging technologies, including Apache Kafka and MapR Streams, with links to sample code Technology choices for streaming analytics: Apache Spark Streaming, Apache Flink, Apache Storm, and Apache Apex How stream-based architectures are helpful to support microservices Specific use cases such as fraud detection and geo-distributed data streams Ted Dunning is Chief Applications Architect at MapR Technologies, and active in the open source community. He currently serves as VP for Incubator at the Apache Foundation, as a champion and mentor for a large number of projects, and as committer and PMC member of the Apache ZooKeeper and Drill projects. Ted is on Twitter as @ted_dunning. Ellen Friedman, a committer for the Apache Drill and Apache Mahout projects, is a solutions consultant and well-known speaker and author, currently writing mainly about big data topics. With a PhD in Biochemistry, she has years of experience as a research scientist and has written about a variety of technical topics. Ellen is on Twitter as @Ellen_Friedman. |
| business rule engine python: The Internet of Things in the Cloud Honbo Zhou, 2013-03-21 Although the Internet of Things (IoT) is a vast and dynamic territory that is evolving rapidly, there has been a need for a book that offers a holistic view of the technologies and applications of the entire IoT spectrum. Filling this void, The Internet of Things in the Cloud: A Middleware Perspective provides a comprehensive introduction to the IoT and its development worldwide. It gives you a panoramic view of the IoT landscape—focusing on the overall technological architecture and design of a tentatively unified IoT framework underpinned by Cloud computing from a middleware perspective. Organized into three sections, it: Describes the many facets of Internet of Things—including the four pillars of IoT and the three layer value chain of IoT Focuses on middleware, the glue and building blocks of a holistic IoT system on every layer of the architecture Explores Cloud computing and IoT as well as their synergy based on the common background of distributed processing The book is based on the author’s two previous bestselling books (in Chinese) on IoT and Cloud computing and more than two decades of hands-on software/middleware programming and architecting experience at organizations such as the Oak Ridge National Laboratory, IBM, BEA Systems, and Silicon Valley startup Doubletwist. Tapping into this wealth of knowledge, the book categorizes the many facets of the IoT and proposes a number of paradigms and classifications about Internet of Things' mass and niche markets and technologies. |
| business rule engine python: Optimization Theory Based on Neutrosophic and Plithogenic Sets Florentin Smarandache, Mohamed Abdel-Basset, 2020-01-14 Optimization Theory Based on Neutrosophic and Plithogenic Sets presents the state-of-the-art research on neutrosophic and plithogenic theories and their applications in various optimization fields. Its table of contents covers new concepts, methods, algorithms, modelling, and applications of green supply chain, inventory control problems, assignment problems, transportation problem, nonlinear problems and new information related to optimization for the topic from the theoretical and applied viewpoints in neutrosophic sets and logic. - All essential topics about neutrosophic optimization and Plithogenic sets make this volume the only single source of comprehensive information - New and innovative theories help researchers solve problems under diverse optimization environments - Varied applications address practitioner fields such as computational intelligence, image processing, medical diagnosis, fault diagnosis, and optimization design |
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| business rule engine python: Python for Mechanical and Aerospace Engineering Alex Kenan, 2021-01-01 The traditional computer science courses for engineering focus on the fundamentals of programming without demonstrating the wide array of practical applications for fields outside of computer science. Thus, the mindset of “Java/Python is for computer science people or programmers, and MATLAB is for engineering” develops. MATLAB tends to dominate the engineering space because it is viewed as a batteries-included software kit that is focused on functional programming. Everything in MATLAB is some sort of array, and it lends itself to engineering integration with its toolkits like Simulink and other add-ins. The downside of MATLAB is that it is proprietary software, the license is expensive to purchase, and it is more limited than Python for doing tasks besides calculating or data capturing. This book is about the Python programming language. Specifically, it is about Python in the context of mechanical and aerospace engineering. Did you know that Python can be used to model a satellite orbiting the Earth? You can find the completed programs and a very helpful 595 page NSA Python tutorial at the book’s GitHub page at https://www.github.com/alexkenan/pymae. Read more about the book, including a sample part of Chapter 5, at https://pymae.github.io |
| business rule engine python: Principles of the Business Rule Approach Ronald G. Ross, 2003 The idea of Business Rules has been around for a while. Simply put, a Business Rule is a statement that defines or constrains some aspect of the business. In practice they are meant to reduce or eliminate the delays, waste, and frustration associated with the IT department having to be involved with almost every action affecting an organization's information systems. The advent of Web services has created renewed interest in them. There are now several well established rules-based products that have demonstrated the effectiveness of their use. But until now there has not been a definitive guide to Business Rules. Ron Ross, considered to be the father of Business Rules, will help organizations apply this powerful solution to their own computer system problems. This book is intended to be the first book that anyone from an IT manager to a business manager will read to understand what Business Rules are, and what how they can be applied to their own situation. |
| business rule engine python: Hands-On Penetration Testing with Python Furqan Khan, 2019-01-31 Implement defensive techniques in your ecosystem successfully with Python Key FeaturesIdentify and expose vulnerabilities in your infrastructure with PythonLearn custom exploit development .Make robust and powerful cybersecurity tools with PythonBook Description With the current technological and infrastructural shift, penetration testing is no longer a process-oriented activity. Modern-day penetration testing demands lots of automation and innovation; the only language that dominates all its peers is Python. Given the huge number of tools written in Python, and its popularity in the penetration testing space, this language has always been the first choice for penetration testers. Hands-On Penetration Testing with Python walks you through advanced Python programming constructs. Once you are familiar with the core concepts, you’ll explore the advanced uses of Python in the domain of penetration testing and optimization. You’ll then move on to understanding how Python, data science, and the cybersecurity ecosystem communicate with one another. In the concluding chapters, you’ll study exploit development, reverse engineering, and cybersecurity use cases that can be automated with Python. By the end of this book, you’ll have acquired adequate skills to leverage Python as a helpful tool to pentest and secure infrastructure, while also creating your own custom exploits. What you will learnGet to grips with Custom vulnerability scanner developmentFamiliarize yourself with web application scanning automation and exploit developmentWalk through day-to-day cybersecurity scenarios that can be automated with PythonDiscover enterprise-or organization-specific use cases and threat-hunting automationUnderstand reverse engineering, fuzzing, buffer overflows , key-logger development, and exploit development for buffer overflows.Understand web scraping in Python and use it for processing web responsesExplore Security Operations Centre (SOC) use casesGet to understand Data Science, Python, and cybersecurity all under one hoodWho this book is for If you are a security consultant , developer or a cyber security enthusiast with little or no knowledge of Python and want in-depth insight into how the pen-testing ecosystem and python combine to create offensive tools , exploits , automate cyber security use-cases and much more then this book is for you. Hands-On Penetration Testing with Python guides you through the advanced uses of Python for cybersecurity and pen-testing, helping you to better understand security loopholes within your infrastructure . |
| business rule engine python: How AI Works Ronald T. Kneusel, 2023-10-24 AI isn’t magic. How AI Works demystifies the explosion of artificial intelligence by explaining—without a single mathematical equation—what happened, when it happened, why it happened, how it happened, and what AI is actually doing under the hood. Artificial intelligence is everywhere—from self-driving cars, to image generation from text, to the unexpected power of language systems like ChatGPT—yet few people seem to know how it all really works. How AI Works unravels the mysteries of artificial intelligence, without the complex math and unnecessary jargon. You’ll learn: The relationship between artificial intelligence, machine learning, and deep learning The history behind AI and why the artificial intelligence revolution is happening now How decades of work in symbolic AI failed and opened the door for the emergence of neural networks What neural networks are, how they are trained, and why all the wonder of modern AI boils down to a simple, repeated unit that knows how to multiply input numbers to produce an output number. The implications of large language models, like ChatGPT and Bard, on our society—nothing will be the same again AI isn’t magic. If you’ve ever wondered how it works, what it can do, or why there’s so much hype, How AI Works will teach you everything you want to know. |
| business rule engine python: Advanced Software and Control for Astronomy Hilton Lewis, Alan Bridger, 2006 Proceedings of SPIE present the original research papers presented at SPIE conferences and other high-quality conferences in the broad-ranging fields of optics and photonics. These books provide prompt access to the latest innovations in research and technology in their respective fields. Proceedings of SPIE are among the most cited references in patent literature. |
| business rule engine python: Building an Effective IoT Ecosystem for Your Business Sudhi R. Sinha, Youngchoon Park, 2017-07-20 This descriptive, practical guide explains how to build a commercially impactful, operationally effective and technically robust IoT ecosystem that takes advantage of the IoT revolution and drives business growth in the consumer IoT as well as industrial internet spaces. With this book, executives, business managers, developers and decision-makers are given the tools to make more informed decisions about IoT solution development, partner eco-system design, and the monetization of products and services. Security and privacy issues are also addressed. Readers will explore the design guidelines and technology choices required to build commercially viable IoT solutions, but also uncover the various monetization and business modeling for connected products. |
| business rule engine python: Handbook of Research on Engineering, Business, and Healthcare Applications of Data Science and Analytics Patil, Bhushan, Vohra, Manisha, 2020-10-23 Analyzing data sets has continued to be an invaluable application for numerous industries. By combining different algorithms, technologies, and systems used to extract information from data and solve complex problems, various sectors have reached new heights and have changed our world for the better. The Handbook of Research on Engineering, Business, and Healthcare Applications of Data Science and Analytics is a collection of innovative research on the methods and applications of data analytics. While highlighting topics including artificial intelligence, data security, and information systems, this book is ideally designed for researchers, data analysts, data scientists, healthcare administrators, executives, managers, engineers, IT consultants, academicians, and students interested in the potential of data application technologies. |
| business rule engine python: Artificial Intelligence with Python Prateek Joshi, 2017-01-27 Build real-world Artificial Intelligence applications with Python to intelligently interact with the world around you About This Book Step into the amazing world of intelligent apps using this comprehensive guide Enter the world of Artificial Intelligence, explore it, and create your own applications Work through simple yet insightful examples that will get you up and running with Artificial Intelligence in no time Who This Book Is For This book is for Python developers who want to build real-world Artificial Intelligence applications. This book is friendly to Python beginners, but being familiar with Python would be useful to play around with the code. It will also be useful for experienced Python programmers who are looking to use Artificial Intelligence techniques in their existing technology stacks. What You Will Learn Realize different classification and regression techniques Understand the concept of clustering and how to use it to automatically segment data See how to build an intelligent recommender system Understand logic programming and how to use it Build automatic speech recognition systems Understand the basics of heuristic search and genetic programming Develop games using Artificial Intelligence Learn how reinforcement learning works Discover how to build intelligent applications centered on images, text, and time series data See how to use deep learning algorithms and build applications based on it In Detail Artificial Intelligence is becoming increasingly relevant in the modern world where everything is driven by technology and data. It is used extensively across many fields such as search engines, image recognition, robotics, finance, and so on. We will explore various real-world scenarios in this book and you'll learn about various algorithms that can be used to build Artificial Intelligence applications. During the course of this book, you will find out how to make informed decisions about what algorithms to use in a given context. Starting from the basics of Artificial Intelligence, you will learn how to develop various building blocks using different data mining techniques. You will see how to implement different algorithms to get the best possible results, and will understand how to apply them to real-world scenarios. If you want to add an intelligence layer to any application that's based on images, text, stock market, or some other form of data, this exciting book on Artificial Intelligence will definitely be your guide! Style and approach This highly practical book will show you how to implement Artificial Intelligence. The book provides multiple examples enabling you to create smart applications to meet the needs of your organization. In every chapter, we explain an algorithm, implement it, and then build a smart application. |
| business rule engine python: Jess in Action Ernest Friedman-Hill, 2003-06-01 Jess in Action first introduces rule programming concepts and teaches you the Jess language. Armed with this knowledge, you then progress through a series of fully-developed applications chosen to expose you to practical rule-based development. The book shows you how you can add power and intelligence to your Java software. |
| business rule engine python: How to Build a Business Rules Engine Malcolm Chisholm, 2004 Demonstrating how to develop a business rules engine, this guide covers user requirements, data modelling, metadata and more. A sample application is used throughout the book to illustrate concepts. The text includes conceptual overview chapters suitable for management-level readers, including a general introduction, business justification, development and implementation considerations and more. Demonstrating how to develop a business rules engine, this guide covers user requirements, data modelling and metadata. It includes conceptual overview chapters suitable for management-level readers, a general introduction, business justification, development and implementation considerations. |
| business rule engine python: IoT Data Analytics using Python M S Hariharan, 2023-10-23 Harness the power of Python to analyze your IoT data KEY FEATURES ● Learn how to build an IoT Data Analytics infrastructure. ● Explore advanced techniques for IoT Data Analysis with Python. ● Gain hands-on experience applying IoT Data Analytics to real-world situations. DESCRIPTION Python is a popular programming language for data analytics, and it is also well-suited for IoT Data Analytics. By leveraging Python's versatility and its rich ecosystem of libraries and tools, Data Analytics for IoT can unlock valuable insights, enable predictive capabilities, and optimize decision-making in various IoT applications and domains. The book begins with a foundation in IoT fundamentals, its role in digital transformation, and why Python is the preferred language for IoT Data Analytics. It then covers essential data analytics concepts, how to establish an IoT Data Analytics environment, and how to design and manage real-time IoT data flows. Next, the book discusses how to implement Descriptive Analytics with Pandas, Time Series Forecasting with Python libraries, and Monitoring, Preventive Maintenance, Optimization, Text Mining, and Automation strategies. It also introduces Edge Computing and Analytics, discusses Continuous and Adaptive Learning concepts, and explores data flow and use cases for Edge Analytics. Finally, the book concludes with a chapter on IoT Data Analytics for self-driving cars, using the CRISP-DM framework for data collection, modeling, and deployment. By the end of the book, you will be equipped with the skills and knowledge needed to extract valuable insights from IoT data and build real-world applications. WHAT YOU WILL LEARN ● Explore the essentials of IoT Data Analytics and the Industry 4.0 revolution. ● Learn how to set up the IoT Data Analytics environment. ● Equip Python developers with data analysis foundations. ● Learn to build data lakes for real-time IoT data streaming. ● Learn to deploy machine learning models on edge devices. ● Understand Edge Computing with MicroPython for efficient IoT Data Analytics. WHO THIS BOOK IS FOR If you are an experienced Python developer who wants to master IoT Data Analytics, or a newcomer who wants to learn Python and its applications in IoT, this book will give you a thorough understanding of IoT Data Analytics and practical skills for real-world use cases. TABLE OF CONTENTS 1. Necessity of Analytics Across IoT 2. Up and Running with Data Analytics Fundamentals 3. Setting Up IoT Analytics Environment 4. Managing Data Pipeline and Cleaning 5. Designing Data Lake and Executing Data Transformation 6. Implementing Descriptive Analytics Using Pandas 7. Time Series Forecasting and Predictions 8. Monitoring and Preventive Maintenance 9. Model Deployment on Edge Devices 10. Understanding Edge Computing with MicroPython 11. IoT Analytics for Self-driving Vehicles |
| business rule engine python: Domain-driven Design Eric Evans, 2004 Domain-Driven Design incorporates numerous examples in Java-case studies taken from actual projects that illustrate the application of domain-driven design to real-world software development. |
| business rule engine python: Business Information Systems Workshops Witold Abramowicz, Leszek Maciaszek, Krzysztof Wecel, 2011-11-18 This book constitutes the refereed proceedings of the three workshops that were organized in conjunction with the International Conference on Business Information Systems, BIS 2011, which took place in Poznań, Poland, June 15-17, 2011. The 18 workshop papers presented were carefully reviewed and selected from 38 submissions. The topics covered are applications and economics of knowledge-based technologies (AKTB), business and IT alignment (BITA), and legal information systems (LIT). In addition, eight papers from the co-located Business Process and Services Computing Conference (BPSC) are also included in this volume. |
| business rule engine python: Databases and Information Systems IV Olegas Vasilecas, Johann Eder, Albertas Caplinskas, 2007 Contains papers that present original results in business modeling and enterprise engineering, database research, data engineering, data quality and data analysis, IS engineering, Web engineering, and application of AI methods. |
| business rule engine python: Knigge für Softwarearchitekten Gernot Starke, Peter Hruschka, 2018-03-02 Gernot Starke und Peter Hruschka laden bereits in der dritten, stark erweiterten Auflage ihres Bestsellers zum Benimmkurs für Softwarearchitekten ein. Also heißt es: Ellenbogen vom Tisch und ran ans Programmieren. Anhand zahlreicher unterhaltsamer und praktischer Beispiele folgt man den beiden erfahrenen Softwareentwicklern auf dem Weg zur besseren Softwarearchitektur – wirkungsvoll, zeitlos und technologieneutral. Die Autoren zeigen auf, wie der Entwickler von heute tickt, sowohl im positiven als auch im negativen Sinne. Die Erfolgsmuster kann man für sich selbst und die eigene Arbeit übernehmen und gleichzeitig aus den Antipatterns lernen, wie man es besser nicht machen sollte. Am Ende des Buchs kennt man auf jeden Fall alle Regeln der Kunst und jeden denkbaren Entwicklertyp, dem man im Berufsalltag begegnen könnte. So steht dem nächsten Projekt nichts (und niemand) mehr im Wege. Dieses Buch richtet sich an alle Softwarearchitekten, denen eine effektive, gut organisierte und kollegiale Arbeitsweise am Herzen liegt und die keine Scheu davor haben, im Zweifelsfall auch einmal ausgetretene Pfade zu verlassen und das eigene Tun zu hinterfragen. |
| business rule engine python: Python for Everybody Charles R. Severance, 2016-04-09 Python for Everybody is designed to introduce students to programming and software development through the lens of exploring data. You can think of the Python programming language as your tool to solve data problems that are beyond the capability of a spreadsheet.Python is an easy to use and easy to learn programming language that is freely available on Macintosh, Windows, or Linux computers. So once you learn Python you can use it for the rest of your career without needing to purchase any software.This book uses the Python 3 language. The earlier Python 2 version of this book is titled Python for Informatics: Exploring Information.There are free downloadable electronic copies of this book in various formats and supporting materials for the book at www.pythonlearn.com. The course materials are available to you under a Creative Commons License so you can adapt them to teach your own Python course. |
| business rule engine python: Knigge für Softwarearchitekten. Reloaded Gernot Starke, Peter Hruschka, 2014-07-10 Dieses Buch zeigt Ihnen unterhaltsame und praxisgerechte Wege zu besseren Softwarearchitekturen - wirkungsvoll, zeitlos und technologieneutral! Sie finden typische Verhaltensmuster von Softwarearchitekten, gute und schlechte. Aus Erfolgsmuster lernen Sie, bessere Systeme zu konstruieren und effektiver zu arbeiten. Aus den „Anti-Patterns“ leiten Sie Abhilfen gegen schlechte Architekturmanieren ab. Ein besonderes Augenmerk liegt auf der Evolution und der Änderung von Systemen. |
| business rule engine python: Rules and Rule Markup Languages for the Semantic Web Asaf Adi, Suzette Stoutenburg, Said Tabet, 2005-11-04 RuleML 2005 was the ?rst international conference on rules and rule markup languages for the Semantic Web, held in conjunction with the International Semantic Web C- ference (ISWC) at Galway, Ireland. With the success of the RuleML workshop series came the need for extended research and applications topics organized in a conference format. RuleML 2005 also accommodated the ?rst Workshop on OWL: Experiences and Directions. Rules are widely recognized to be a major part of the frontier of the Semantic Web, and critical to the early adoption and applications of knowledge-based techniques in- business, especially enterprise integration and B2B e-commerce. This includes kno- edge representation (KR) theory and algorithms; markup languages based on such KR; engines, translators, and other tools; relationships to standardization efforts; and, not least, applications. Interest and activity in the area of rules for the Semantic Web has grown rapidly over the last ?ve years. The RuleML 2005 Conference was aimed to be this year’s premiere scienti?c conference on the topic. It continued in topic, leadership, and collaboration with the previous series of three highly successful annual inter- tional workshops (RuleML 2004, RuleML 2003 and RuleML 2002). The theme for RuleML 2005 was rule languages for reactive and proactive rules, complex event p- cessing, and event-driven rules, to support the emergence of Semantic Web applications. Special highlights of the RuleML 2005 conference included the keynote address by Sir Tim Berners- Lee, Director of W3C. |
| business rule engine python: The Cloud Security Ecosystem Raymond Choo, Ryan Ko, 2015-06-01 Drawing upon the expertise of world-renowned researchers and experts, The Cloud Security Ecosystem comprehensively discusses a range of cloud security topics from multi-disciplinary and international perspectives, aligning technical security implementations with the most recent developments in business, legal, and international environments. The book holistically discusses key research and policy advances in cloud security – putting technical and management issues together with an in-depth treaties on a multi-disciplinary and international subject. The book features contributions from key thought leaders and top researchers in the technical, legal, and business and management aspects of cloud security. The authors present the leading edge of cloud security research, covering the relationships between differing disciplines and discussing implementation and legal challenges in planning, executing, and using cloud security. - Presents the most current and leading-edge research on cloud security from a multi-disciplinary standpoint, featuring a panel of top experts in the field - Focuses on the technical, legal, and business management issues involved in implementing effective cloud security, including case examples - Covers key technical topics, including cloud trust protocols, cryptographic deployment and key management, mobile devices and BYOD security management, auditability and accountability, emergency and incident response, as well as cloud forensics - Includes coverage of management and legal issues such as cloud data governance, mitigation and liability of international cloud deployment, legal boundaries, risk management, cloud information security management plans, economics of cloud security, and standardization efforts |
| business rule engine python: Advances in Information Systems, Artificial Intelligence and Knowledge Management Inès Saad, Camille Rosenthal-Sabroux, Faiez Gargouri, Salem Chakhar, Nigel Williams, Ella Haig, 2024-02-20 This book constitutes the refereed proceedings of the 6th International Conference on Information and Knowledge Systems, ICIKS 2023, held in Portsmouth, UK, during June 22–23, 2023. The 18 full papers and 6 short papers included in this book were carefully reviewed and selected from 58 submissions. They were organized in topical sections as follows: Decision Making, Recommender Systems, and Information Support Systems; Information Systems and Machine Learning; Knowledge Management, Context and Ontology; Cybersecurity and Intelligent Systems; and Natural Language Processing for Decision Systems. |
| business rule engine python: Python for Finance Yves J. Hilpisch, 2018-12-05 The financial industry has recently adopted Python at a tremendous rate, with some of the largest investment banks and hedge funds using it to build core trading and risk management systems. Updated for Python 3, the second edition of this hands-on book helps you get started with the language, guiding developers and quantitative analysts through Python libraries and tools for building financial applications and interactive financial analytics. Using practical examples throughout the book, author Yves Hilpisch also shows you how to develop a full-fledged framework for Monte Carlo simulation-based derivatives and risk analytics, based on a large, realistic case study. Much of the book uses interactive IPython Notebooks. |
| business rule engine python: 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. |
| business rule engine python: Business Analytics and Decision Making in Practice Ali Emrouznejad, |
| business rule engine python: Learn Python 3 the Hard Way Zed A. Shaw, 2017-06-26 You Will Learn Python 3! Zed Shaw has perfected the world’s best system for learning Python 3. Follow it and you will succeed—just like the millions of beginners Zed has taught to date! You bring the discipline, commitment, and persistence; the author supplies everything else. In Learn Python 3 the Hard Way, you’ll learn Python by working through 52 brilliantly crafted exercises. Read them. Type their code precisely. (No copying and pasting!) Fix your mistakes. Watch the programs run. As you do, you’ll learn how a computer works; what good programs look like; and how to read, write, and think about code. Zed then teaches you even more in 5+ hours of video where he shows you how to break, fix, and debug your code—live, as he’s doing the exercises. Install a complete Python environment Organize and write code Fix and break code Basic mathematics Variables Strings and text Interact with users Work with files Looping and logic Data structures using lists and dictionaries Program design Object-oriented programming Inheritance and composition Modules, classes, and objects Python packaging Automated testing Basic game development Basic web development It’ll be hard at first. But soon, you’ll just get it—and that will feel great! This course will reward you for every minute you put into it. Soon, you’ll know one of the world’s most powerful, popular programming languages. You’ll be a Python programmer. This Book Is Perfect For Total beginners with zero programming experience Junior developers who know one or two languages Returning professionals who haven’t written code in years Seasoned professionals looking for a fast, simple, crash course in Python 3 |
| business rule engine python: Deep Learning with Python Francois Chollet, 2017-11-30 Summary Deep Learning with Python introduces the field of deep learning using the Python language and the powerful Keras library. Written by Keras creator and Google AI researcher François Chollet, this book builds your understanding through intuitive explanations and practical examples. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the Technology Machine learning has made remarkable progress in recent years. We went from near-unusable speech and image recognition, to near-human accuracy. We went from machines that couldn't beat a serious Go player, to defeating a world champion. Behind this progress is deep learning—a combination of engineering advances, best practices, and theory that enables a wealth of previously impossible smart applications. About the Book Deep Learning with Python introduces the field of deep learning using the Python language and the powerful Keras library. Written by Keras creator and Google AI researcher François Chollet, this book builds your understanding through intuitive explanations and practical examples. You'll explore challenging concepts and practice with applications in computer vision, natural-language processing, and generative models. By the time you finish, you'll have the knowledge and hands-on skills to apply deep learning in your own projects. What's Inside Deep learning from first principles Setting up your own deep-learning environment Image-classification models Deep learning for text and sequences Neural style transfer, text generation, and image generation About the Reader Readers need intermediate Python skills. No previous experience with Keras, TensorFlow, or machine learning is required. About the Author François Chollet works on deep learning at Google in Mountain View, CA. He is the creator of the Keras deep-learning library, as well as a contributor to the TensorFlow machine-learning framework. He also does deep-learning research, with a focus on computer vision and the application of machine learning to formal reasoning. His papers have been published at major conferences in the field, including the Conference on Computer Vision and Pattern Recognition (CVPR), the Conference and Workshop on Neural Information Processing Systems (NIPS), the International Conference on Learning Representations (ICLR), and others. Table of Contents PART 1 - FUNDAMENTALS OF DEEP LEARNING What is deep learning? Before we begin: the mathematical building blocks of neural networks Getting started with neural networks Fundamentals of machine learning PART 2 - DEEP LEARNING IN PRACTICE Deep learning for computer vision Deep learning for text and sequences Advanced deep-learning best practices Generative deep learning Conclusions appendix A - Installing Keras and its dependencies on Ubuntu appendix B - Running Jupyter notebooks on an EC2 GPU instance |
BUSINESS | English meaning - Cambridge Dictionary
BUSINESS definition: 1. the activity of buying and selling goods and services: 2. a particular company that buys and….
VENTURE | English meaning - Cambridge Dictionary
VENTURE definition: 1. a new activity, usually in business, that involves risk or uncertainty: 2. to risk going….
ENTERPRISE | English meaning - Cambridge Dictionary
ENTERPRISE definition: 1. an organization, especially a business, or a difficult and important plan, especially one that….
INCUMBENT | English meaning - Cambridge Dictionary
INCUMBENT definition: 1. officially having the named position: 2. to be necessary for someone: 3. the person who has or….
AD HOC | English meaning - Cambridge Dictionary
AD HOC definition: 1. made or happening only for a particular purpose or need, not planned before it happens: 2. made….
LEVERAGE | English meaning - Cambridge Dictionary
LEVERAGE definition: 1. the action or advantage of using a lever: 2. power to influence people and get the results you….
ENTREPRENEUR | English meaning - Cambridge Dictionary
ENTREPRENEUR definition: 1. someone who starts their own business, especially when this involves seeing a new opportunity….
CULTIVATE | English meaning - Cambridge Dictionary
CULTIVATE definition: 1. to prepare land and grow crops on it, or to grow a particular crop: 2. to try to develop and….
EQUITY | English meaning - Cambridge Dictionary
EQUITY definition: 1. the value of a company, divided into many equal parts owned by the shareholders, or one of the….
LIAISE | English meaning - Cambridge Dictionary
LIAISE definition: 1. to speak to people in other organizations, etc. in order to work with them or exchange….
BUSINESS | English meaning - Cambridge Dictionary
BUSINESS definition: 1. the activity of buying and selling goods and services: 2. a particular company that buys and….
VENTURE | English meaning - Cambridge Dictionary
VENTURE definition: 1. a new activity, usually in business, that involves risk or uncertainty: 2. to risk going….
ENTERPRISE | English meaning - Cambridge Dictionary
ENTERPRISE definition: 1. an organization, especially a business, or a difficult and important plan, especially one that….
INCUMBENT | English meaning - Cambridge Dictionary
INCUMBENT definition: 1. officially having the named position: 2. to be necessary for someone: 3. the person who has or….
AD HOC | English meaning - Cambridge Dictionary
AD HOC definition: 1. made or happening only for a particular purpose or need, not planned before it happens: 2. made….
LEVERAGE | English meaning - Cambridge Dictionary
LEVERAGE definition: 1. the action or advantage of using a lever: 2. power to influence people and get the results you….
ENTREPRENEUR | English meaning - Cambridge Dictionary
ENTREPRENEUR definition: 1. someone who starts their own business, especially when this involves seeing a new opportunity….
CULTIVATE | English meaning - Cambridge Dictionary
CULTIVATE definition: 1. to prepare land and grow crops on it, or to grow a particular crop: 2. to try to develop and….
EQUITY | English meaning - Cambridge Dictionary
EQUITY definition: 1. the value of a company, divided into many equal parts owned by the shareholders, or one of the….
LIAISE | English meaning - Cambridge Dictionary
LIAISE definition: 1. to speak to people in other organizations, etc. in order to work with them or exchange….
