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| data science masters usc: Translational Biomedical Informatics Bairong Shen, Haixu Tang, Xiaoqian Jiang, 2016-10-31 This book introduces readers to essential methods and applications in translational biomedical informatics, which include biomedical big data, cloud computing and algorithms for understanding omics data, imaging data, electronic health records and public health data. The storage, retrieval, mining and knowledge discovery of biomedical big data will be among the key challenges for future translational research. The paradigm for precision medicine and healthcare needs to integratively analyze not only the data at the same level – e.g. different omics data at the molecular level – but also data from different levels – the molecular, cellular, tissue, clinical and public health level. This book discusses the following major aspects: the structure of cross-level data; clinical patient information and its shareability; and standardization and privacy. It offers a valuable guide for all biologists, biomedical informaticians and clinicians with an interest in Precision Medicine Informatics. |
| data science masters usc: Deep Learning and Its Applications Arvind Kumar Tiwari, 2021 In just the past five years, deep learning has taken the world by surprise, driving rapid progress in fields as diverse as computer vision, natural language processing, automatic speech recognition, etc. This book presents an introduction to deep learning and various applications of deep learning such as recommendation systems, text recognition, diabetic retinopathy prediction of breast cancer, prediction of epilepsy, sentiment, fake news detection, software defect prediction and protein function prediction-- |
| data science masters usc: CBEST Test Preparation Test Prep Books, 2017-05 Test Prep Book's CBEST Test Preparation Study Questions 2018 & 2019: Three Full-Length CBEST Practice Tests for the California Basic Educational Skills Test Developed by Test Prep Books for test takers trying to achieve a passing score on the CBEST exam, this comprehensive study guide includes: -Quick Overview -Test-Taking Strategies -Introduction -CBEST Practice Test #1 -Answer Explanations #1 -CBEST Practice Test #2 -Answer Explanations #2 -CBEST Practice Test #3 -Answer Explanations #3 Disclaimer: CBEST(R) is a registered trademark of California Basic Educational Skills Test, which was not involved in the production of, and does not endorse, this product. Each section of the test has a comprehensive review created by Test Prep Books that goes into detail to cover all of the content likely to appear on the CBEST test. The Test Prep Books CBEST practice test questions are each followed by detailed answer explanations. If you miss a question, it's important that you are able to understand the nature of your mistake and how to avoid making it again in the future. The answer explanations will help you to learn from your mistakes and overcome them. Understanding the latest test-taking strategies is essential to preparing you for what you will expect on the exam. A test taker has to not only understand the material that is being covered on the test, but also must be familiar with the strategies that are necessary to properly utilize the time provided and get through the test without making any avoidable errors. Test Prep Books has drilled down the top test-taking tips for you to know. Anyone planning to take this exam should take advantage of the CBEST test prep review material, practice test questions, and test-taking strategies contained in this Test Prep Books study guide. |
| data science masters usc: Careers in Information Science Louise Schultz, 1963 Presents copy for use as a reference brochure and a giveaway sheet to be distributed to guidance counselors to help them direct young people into the growing field of Information Science. Sets forth that Information Science is concerned with the properties, behavior, and flow of information. Describes how it is used, both by individuals and in large systems. Discusses the opportunities in Information Science and outlines three relatively different career areas: (1) Special Librarianship; (2) Literature Analysis; and (3) Information System Design. Details an educational program appropriate for participation in these career areas. Concludes that Information Science is a new but rapidly growing field pushing the frontiers of human knowledge and, thus, contributing to human well-being and progress. (Author). |
| data science masters usc: Web Technologies and Applications Weihong Han, Zi Huang, Changjun Hu, Hongli Zhang, Li Guo, 2014-08-15 This book constitutes the refereed proceedings of the workshops held at the 16th Asia-Pacific Web Conference, APWeb 2014, in Changsha, China, in September 2014. The 34 full papers were carefully reviewed and selected from 59 submissions. This volume presents the papers that have been accepted for the following workshops: First International Workshop on Social Network Analysis, SNA 2014; First International Workshop on Network and Information Security, NIS 2014; First International Workshop on Internet of Things Search, IoTS 2014. The papers cover various issues in social network analysis, security and information retrieval against the heterogeneous big data. |
| data science masters usc: Left to Their Own Devices Julie M. Albright, 2019-04-16 A sociologist explores the many ways that digital natives' interaction with technology has changed their relationship with people, places, jobs, and other stabilizing structures and created a new way of life that is at odds with the American Dream of past generations. Digital natives are hacking the American Dream. Young people brought up with the Internet, smartphones, and social media are quickly rendering old habits, values, behaviors, and norms a distant memory--creating the greatest generation gap in history. In this eye-opening book, digital sociologist Julie M. Albright looks at the many ways in which younger people, facilitated by technology, are coming untethered from traditional aspirations and ideals, and asks: What are the effects of being disconnected from traditional, stabilizing social structures like churches, marriage, political parties, and long-term employment? What does it mean to be human when one's ties to people, places, jobs, and societal institutions are weakened or broken, displaced by digital hyper-connectivity? Albright sees both positives and negatives. On the one hand, mobile connectivity has given digital nomads the unprecedented opportunity to work or live anywhere. But, new threats to well-being are emerging, including increased isolation, anxiety, and loneliness, decreased physical exercise, ephemeral relationships, fragmented attention spans, and detachment from the calm of nature. In this time of rapid, global, technologically driven change, this book offers fresh insights into the unintended societal and psychological implications of lives exclusively lived in a digital world. |
| data science masters usc: Lifestyle Redesign , 2015 |
| data science masters usc: Sports Performance Measurement and Analytics Lorena Martin, 2016-02-03 A PRACTICAL, REAL-WORLD GUIDE TO ANALYTICS FOR THE 5 MAJOR SPORTS: FOOTBALL, BASKETBALL, BASEBALL, SOCCER, AND TENNIS GAIN A COMPETITIVE EDGE! This is the first real-world guide to building and using analytical models for measuring and assessing performance in the five major sports: football, basketball, baseball, soccer, and tennis. Unlike books that focus strictly on theory, this book brings together sports measurement and statistical analyses, demonstrating how to examine differences across sports as well as between player positions. This book will provide you with the tools for cutting-edge approaches you can extend to the sport of your choice. Expert Northwestern University data scientist, UC San Diego researcher, and competitive athlete, Lorena Martin shows how to use measures and apply statistical models to evaluate players, reduce injuries, and improve sports performance. You’ll learn how to leverage a deep understanding of each sport’s principles, rules, attributes, measures, and performance outcomes. Sports Performance Measurement and Analytics will be an indispensable resource for anyone who wants to bring analytical rigor to athletic competition: students, professors, analysts, fans, physiologists, coaches, managers, and sports executives alike. All data sets, extensive code, and additional examples are available for download at http://www.ftpress.com/martin/ What are the qualities a person must have to become a world-class athlete? This question and many more can be answered through research, measurement, statistics, and analytics. This book gives athletes, trainers, coaches, and managers a better understanding of measurement and analytics as they relate to sports performance. To develop accurate measures, we need to know what we want to measure and why. There is great power in accurate measures and statistics. Research findings can show us how to prevent injuries, evaluate strengths and weaknesses, improve team cohesion, and optimize sports performance. This book serves many readers. People involved with sports will gain an appreciation for performance measures and analytics. People involved with analytics will gain new insights into quantified values representing physical, physiological, and psychological components of sports performance. And students eager to learn about sports analytics will have a practical introduction to the field. This is a thorough introduction to performance measurement and analytics for five of the world’s leading sports. The only book of its kind, it offers a complete overview of the most important concepts, rules, measurements, and statistics for each sport, while demonstrating applications of real-world analytics. You’ll find practical, state-of-the-art guidance on predicting future outcomes, evaluating an athlete’s market value, and more. |
| data science masters usc: Knowledge Graphs Mayank Kejriwal, Craig A. Knoblock, Pedro Szekely, 2021-03-30 A rigorous and comprehensive textbook covering the major approaches to knowledge graphs, an active and interdisciplinary area within artificial intelligence. The field of knowledge graphs, which allows us to model, process, and derive insights from complex real-world data, has emerged as an active and interdisciplinary area of artificial intelligence over the last decade, drawing on such fields as natural language processing, data mining, and the semantic web. Current projects involve predicting cyberattacks, recommending products, and even gleaning insights from thousands of papers on COVID-19. This textbook offers rigorous and comprehensive coverage of the field. It focuses systematically on the major approaches, both those that have stood the test of time and the latest deep learning methods. |
| data science masters usc: Foundations of Machine Learning, second edition Mehryar Mohri, Afshin Rostamizadeh, Ameet Talwalkar, 2018-12-25 A new edition of a graduate-level machine learning textbook that focuses on the analysis and theory of algorithms. This book is a general introduction to machine learning that can serve as a textbook for graduate students and a reference for researchers. It covers fundamental modern topics in machine learning while providing the theoretical basis and conceptual tools needed for the discussion and justification of algorithms. It also describes several key aspects of the application of these algorithms. The authors aim to present novel theoretical tools and concepts while giving concise proofs even for relatively advanced topics. Foundations of Machine Learning is unique in its focus on the analysis and theory of algorithms. The first four chapters lay the theoretical foundation for what follows; subsequent chapters are mostly self-contained. Topics covered include the Probably Approximately Correct (PAC) learning framework; generalization bounds based on Rademacher complexity and VC-dimension; Support Vector Machines (SVMs); kernel methods; boosting; on-line learning; multi-class classification; ranking; regression; algorithmic stability; dimensionality reduction; learning automata and languages; and reinforcement learning. Each chapter ends with a set of exercises. Appendixes provide additional material including concise probability review. This second edition offers three new chapters, on model selection, maximum entropy models, and conditional entropy models. New material in the appendixes includes a major section on Fenchel duality, expanded coverage of concentration inequalities, and an entirely new entry on information theory. More than half of the exercises are new to this edition. |
| data science masters usc: Time Series Econometrics Pierre Perron, 2018 Part I. Unit roots and trend breaks -- Part II. Structural change |
| data science masters usc: The Birds of America John James Audubon, 1842 This edition has 65 new images, making a total of 500. The original configurations were altered so that there is only one species per plate. The text is a revision of the Ornithological Biography, rearranged according to Audubon's Synopsis of the Birds of North America (1839). |
| data science masters usc: Direct Loans , 1996 |
| data science masters usc: Tika in Action Jukka L. Zitting, Chris Mattmann, 2011-11-30 Summary Tika in Action is a hands-on guide to content mining with Apache Tika. The book's many examples and case studies offer real-world experience from domains ranging from search engines to digital asset management and scientific data processing. About the Technology Tika is an Apache toolkit that has built into it everything you and your app need to know about file formats. Using Tika, your applications can discover and extract content from digital documents in almost any format, including exotic ones. About this Book Tika in Action is the ultimate guide to content mining using Apache Tika. You'll learn how to pull usable information from otherwise inaccessible sources, including internet media and file archives. This example-rich book teaches you to build and extend applications based on real-world experience with search engines, digital asset management, and scientific data processing. In addition to architectural overviews, you'll find detailed chapters on features like metadata extraction, automatic language detection, and custom parser development. This book is written for developers who are new to both Scala and Lift and covers just enough Scala to get you started. 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 Crack MS Word, PDF, HTML, and ZIP Integrate with search engines, CMS, and other data sources Learn through experimentation Many examples This book requires no previous knowledge of Tika or text mining techniques. It assumes a working knowledge of Java. ========================================== Table of Contents PART 1 GETTING STARTED The case for the digital Babel fish Getting started with Tika The information landscape PART 2 TIKA IN DETAIL Document type detection Content extraction Understanding metadata Language detection What's in a file? PART 3 INTEGRATION AND ADVANCED USE The big picture Tika and the Lucene search stack Extending Tika PART 4 CASE STUDIES Powering NASA science data systems Content management with Apache Jackrabbit Curating cancer research data with Tika The classic search engine example |
| data science masters usc: American Shtetl Nomi M. Stolzenberg, David N. Myers, 2022-02-08 A compelling account of how a group of Hasidic Jews established its own local government on American soil Settled in the mid-1970s by a small contingent of Hasidic families, Kiryas Joel is an American town with few parallels in Jewish history—but many precedents among religious communities in the United States. This book tells the story of how this group of pious, Yiddish-speaking Jews has grown to become a thriving insular enclave and a powerful local government in upstate New York. While rejecting the norms of mainstream American society, Kiryas Joel has been stunningly successful in creating a world apart by using the very instruments of secular political and legal power that it disavows. Nomi Stolzenberg and David Myers paint a richly textured portrait of daily life in Kiryas Joel, exploring the community's guiding religious, social, and economic norms. They delve into the roots of Satmar Hasidism and its charismatic founder, Rebbe Joel Teitelbaum, following his journey from nineteenth-century Hungary to post–World War II Brooklyn, where he dreamed of founding an ideal Jewish town modeled on the shtetls of eastern Europe. Stolzenberg and Myers chart the rise of Kiryas Joel as an official municipality with its own elected local government. They show how constant legal and political battles defined and even bolstered the community, whose very success has coincided with the rise of political conservatism and multiculturalism in American society over the past forty years. Timely and accessible, American Shtetl unravels the strands of cultural and legal conflict that gave rise to one of the most vibrant religious communities in America, and reveals a way of life shaped by both self-segregation and unwitting assimilation. |
| data science masters usc: The American Research University from World War II to World Wide Web Charles M. Vest, 2007-06-01 Forty years after Clark Kerr coined the term multiversity, the American research university has continued to evolve into a complex force for social and economic good. This volume provides a unique opportunity to explore the current state of the research university system. Charles M. Vest, one of the leading advocates for autonomy for American higher education, offers a multifaceted view of the university at the beginning of a new century. With a complex mission and funding structure, the university finds its international openness challenged by new security concerns and its ability to contribute to worldwide opportunity through sharing and collaboration dramatically expanded by the Internet. In particular, Vest addresses the need to nurture broad access to our universities and stay true to the fundamental mission of creating opportunity. |
| data science masters usc: Reservoir Characterization Larry Lake, 2012-12-02 Reservoir Characterization is a collection of papers presented at the Reservoir Characterization Technical Conference, held at the Westin Hotel-Galleria in Dallas on April 29-May 1, 1985. Conference held April 29-May 1, 1985, at the Westin Hotel—Galleria in Dallas. The conference was sponsored by the National Institute for Petroleum and Energy Research, Bartlesville, Oklahoma. Reservoir characterization is a process for quantitatively assigning reservoir properties, recognizing geologic information and uncertainties in spatial variability. This book contains 19 chapters, and begins with the geological characterization of sandstone reservoir, followed by the geological prediction of shale distribution within the Prudhoe Bay field. The subsequent chapters are devoted to determination of reservoir properties, such as porosity, mineral occurrence, and permeability variation estimation. The discussion then shifts to the utility of a Bayesian-type formalism to delineate qualitative soft information and expert interpretation of reservoir description data. This topic is followed by papers concerning reservoir simulation, parameter assignment, and method of calculation of wetting phase relative permeability. This text also deals with the role of discontinuous vertical flow barriers in reservoir engineering. The last chapters focus on the effect of reservoir heterogeneity on oil reservoir. Petroleum engineers, scientists, and researchers will find this book of great value. |
| data science masters usc: Ranked Set Sampling Munir Ahmad, M. Hanif, Hassen A. Muttlak, 2010-09-13 Ranked Set Sampling is one of the new areas of study in this region of the world and is a growing subject of research. Recently, researchers have paid attention to the development of the types of sampling; though it was not welcome in the beginning, it has numerous advantages over the classical sampling techniques. Ranked Set Sampling is doubly random and can be used in any survey designs. The Pakistan Journal of Statistics had attracted statisticians and samplers around the world to write up aspects of Ranked Set Sampling. All of the essays in this book have been reviewed by many critics. This volume can be used as a reference book for postgraduate students in economics, social sciences, medical and biological sciences, and statistics. The subject is still a hot topic for MPhil and PhD students for their dissertations. |
| data science masters usc: Tax Politics and Policy Michael Thom, 2017-02-03 Taxes are an inescapable part of life. They are perhaps the most economically consequential aspect of the relationship between individuals and their government. Understanding tax development and implementation, not to mention the political forces involved, is critical to fully appreciating and critiquing that relationship. Tax Politics and Policy offers a comprehensive survey of taxation in the United States. It explores competing theories of taxation’s role in civil society; investigates the evolution and impact of taxes on income, consumption, and assets; and highlights the role of interest groups in tax policy. This is the first book to include a separate look at sin taxes on tobacco, alcohol, marijuana, and sugar. The book concludes with a look at tax reform ideas, both old and new. This book is written for a broad audience—from upper-level undergraduates to graduate students in public policy, public administration, political science, economics, and related fields—and anyone else that has ever paid taxes. |
| data science masters usc: Methods in Genomic Neuroscience Hemin R. Chin, Steven O. Moldin, 2001-09-26 The past few years have witnessed extraordinary advances in molecular genetic techniques and the accumulation of structural genomics information and resources in both human and model organisms. With the development of new technologies and the availability of resources like the sequence of eukaryotic genomes, problems of a previously unthinkable sco |
| data science masters usc: Health Professions Student Loan Program , 1984 |
| data science masters usc: Fit to be Citizens? Natalia Molina, 2006 Shows how science and public health shaped the meaning of race in the early twentieth century. Examining the experiences of Mexican, Japanese, and Chinese immigrants in Los Angeles, this book illustrates the ways health officials used complexly constructed concerns about public health to demean, diminish, discipline, and define racial groups. |
| data science masters usc: Unrelenting Innovation Gerard J. Tellis, 2013-01-04 The hands-on guide for fostering relentless innovation within your company Gerard Tellis, a noted expert on innovation, advertising, and global markets, makes the compelling case that the culture of a firm is the crucial driver of an organization's innovativeness. In this groundbreaking book he describes the three traits and three practices necessary to create a culture of relentless innovation. Organizations must be willing to cannibalize successful products, embrace risk, and focus on the future. Organizations build these traits by providing incentives for enterprise, empowering product champions, and encouraging internal markets. Spelling out the critical role of culture, the author provides illustrative examples of organizations with winning cultures and explores the theory and evidence for each of the six components of culture. The book concludes with a discussion of why culture is superior to alternate theories for fostering innovation. Offers a groundbreaking take on innovation that is driven by a company's culture Shows what it takes to create a culture of innovation within any organization Based on a study of 770 companies across 15 countries, the origin of 90 radical innovations spanning over 100 years, and the evolution of 66 markets spanning over a 100 years Provides numerous mini cases to illustrate the workings of culture Written by Gerard Tellis director of the Center for Global Innovation This must-have resource clearly shows the role of culture in driving relentless innovation and how to foster it within any organization. |
| data science masters usc: Designing the New American University Michael M. Crow, William B. Dabars, 2015-03-15 A radical blueprint for reinventing American higher education. America’s research universities consistently dominate global rankings but may be entrenched in a model that no longer accomplishes their purposes. With their multiple roles of discovery, teaching, and public service, these institutions represent the gold standard in American higher education, but their evolution since the nineteenth century has been only incremental. The need for a new and complementary model that offers broader accessibility to an academic platform underpinned by knowledge production is critical to our well-being and economic competitiveness. Michael M. Crow, president of Arizona State University and an outspoken advocate for reinventing the public research university, conceived the New American University model when he moved from Columbia University to Arizona State in 2002. Following a comprehensive reconceptualization spanning more than a decade, ASU has emerged as an international academic and research powerhouse that serves as the foundational prototype for the new model. Crow has led the transformation of ASU into an egalitarian institution committed to academic excellence, inclusiveness to a broad demographic, and maximum societal impact. In Designing the New American University, Crow and coauthor William B. Dabars—a historian whose research focus is the American research university—examine the emergence of this set of institutions and the imperative for the new model, the tenets of which may be adapted by colleges and universities, both public and private. Through institutional innovation, say Crow and Dabars, universities are apt to realize unique and differentiated identities, which maximize their potential to generate the ideas, products, and processes that impact quality of life, standard of living, and national economic competitiveness. Designing the New American University will ignite a national discussion about the future evolution of the American research university. |
| data science masters usc: The Inside Track to Careers in Real Estate Stan Ross, James Carberry, 2006 Real estate can be a lucrative industry-known for making deals, moguls, and millionaires. If your goal is to have a potentially high-paying job in an exciting business, this book will help you determine if a career in real estate is right for you and how to get started. Focusing on careers for college graduates, the book is packed with information on the wealth of job opportunities in the industry-including development, finance, asset management, international opportunities, starting your own real estate company-and the possible career paths you can take to meet your goals. Candid interviews with top industry leaders, as well as recent graduates, offer practical tips and advice on what a career in real estate is really like, how to get your first job, and what it takes to be successful. Book jacket. |
| data science masters usc: 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. |
| data science masters usc: Analytics and Knowledge Management Suliman Hawamdeh, Hsia-Ching Chang, 2018-08-06 The process of transforming data into actionable knowledge is a complex process that requires the use of powerful machines and advanced analytics technique. Analytics and Knowledge Management examines the role of analytics in knowledge management and the integration of big data theories, methods, and techniques into an organizational knowledge management framework. Its chapters written by researchers and professionals provide insight into theories, models, techniques, and applications with case studies examining the use of analytics in organizations. The process of transforming data into actionable knowledge is a complex process that requires the use of powerful machines and advanced analytics techniques. Analytics, on the other hand, is the examination, interpretation, and discovery of meaningful patterns, trends, and knowledge from data and textual information. It provides the basis for knowledge discovery and completes the cycle in which knowledge management and knowledge utilization happen. Organizations should develop knowledge focuses on data quality, application domain, selecting analytics techniques, and on how to take actions based on patterns and insights derived from analytics. Case studies in the book explore how to perform analytics on social networking and user-based data to develop knowledge. One case explores analyze data from Twitter feeds. Another examines the analysis of data obtained through user feedback. One chapter introduces the definitions and processes of social media analytics from different perspectives as well as focuses on techniques and tools used for social media analytics. Data visualization has a critical role in the advancement of modern data analytics, particularly in the field of business intelligence and analytics. It can guide managers in understanding market trends and customer purchasing patterns over time. The book illustrates various data visualization tools that can support answering different types of business questions to improve profits and customer relationships. This insightful reference concludes with a chapter on the critical issue of cybersecurity. It examines the process of collecting and organizing data as well as reviewing various tools for text analysis and data analytics and discusses dealing with collections of large datasets and a great deal of diverse data types from legacy system to social networks platforms. |
| data science masters usc: Data Science & Business Analytics Sneha Kumari, K. K. Tripathy, Vidya Kumbhar, 2020-12-04 Data Science & Business Analytics explores the application of big data and business analytics by academics, researchers, industrial experts, policy makers and practitioners, helping the reader to understand how big data can be efficiently utilized in better managerial applications. |
| data science masters usc: Transformative Ethnic Studies in Schools Christine E. Sleeter, Miguel Zavala, 2020 Drawing on Christine Sleeter's review of research on the academic and social impact of ethnic studies commissioned by the National Education Association, this book will examine the value and forms of teaching and researching ethnic studies. The book employs a diverse conceptual framework, including critical pedagogy, anti-racism, Afrocentrism, Indigeneity, youth participatory action research, and critical multicultural education. The book provides cases of classroom teachers to 'illustrate what such conceptual framework look like when enacted in the classroom, as well as tensions that spring from them within school bureaucracies driven by neoliberalism.' Sleeter and Zavala will also outline ways to conduct research for 'investigating both learning and broader impacts of ethnic research used for liberatory ends'-- |
| data science masters usc: Supply Chain and Logistics Management Made Easy Paul Myerson, 2015 This easy guide introduces the modern field of supply chain and logistics management, explains why it is central to business success, shows how its pieces fit together, and presents best practices you can use wherever you work. Myerson explains key concepts, tools, and applications in clear, simple language, with intuitive examples that make sense to any student or professional. |
| data science masters usc: Bioinformatics Algorithms Phillip Compeau, Pavel Pevzner, 1986-06 Bioinformatics Algorithms: an Active Learning Approach is one of the first textbooks to emerge from the recent Massive Online Open Course (MOOC) revolution. A light-hearted and analogy-filled companion to the authors' acclaimed online course (http://coursera.org/course/bioinformatics), this book presents students with a dynamic approach to learning bioinformatics. It strikes a unique balance between practical challenges in modern biology and fundamental algorithmic ideas, thus capturing the interest of students of biology and computer science students alike.Each chapter begins with a central biological question, such as Are There Fragile Regions in the Human Genome? or Which DNA Patterns Play the Role of Molecular Clocks? and then steadily develops the algorithmic sophistication required to answer this question. Hundreds of exercises are incorporated directly into the text as soon as they are needed; readers can test their knowledge through automated coding challenges on Rosalind (http://rosalind.info), an online platform for learning bioinformatics.The textbook website (http://bioinformaticsalgorithms.org) directs readers toward additional educational materials, including video lectures and PowerPoint slides. |
| data science masters usc: VLSI Design M. Michael Vai, 2017-12-19 Very Large Scale Integration (VLSI) has become a necessity rather than a specialization for electrical and computer engineers. This unique text provides Engineering and Computer Science students with a comprehensive study of the subject, covering VLSI from basic design techniques to working principles of physical design automation tools to leading edge application-specific array processors. Beginning with CMOS design, the author describes VLSI design from the viewpoint of a digital circuit engineer. He develops physical pictures for CMOS circuits and demonstrates the top-down design methodology using two design projects - a microprocessor and a field programmable gate array. The author then discusses VLSI testing and dedicates an entire chapter to the working principles, strengths, and weaknesses of ubiquitous physical design tools. Finally, he unveils the frontiers of VLSI. He emphasizes its use as a tool to develop innovative algorithms and architecture to solve previously intractable problems. VLSI Design answers not only the question of what is VLSI, but also shows how to use VLSI. It provides graduate and upper level undergraduate students with a complete and congregated view of VLSI engineering. |
| data science masters usc: Algorithm Design Jon Kleinberg, Eva Tardos, 2013-08-29 Algorithm Design introduces algorithms by looking at the real-world problems that motivate them. The book teaches students a range of design and analysis techniques for problems that arise in computing applications. The text encourages an understanding of the algorithm design process and an appreciation of the role of algorithms in the broader field of computer science. The full text downloaded to your computer With eBooks you can: search for key concepts, words and phrases make highlights and notes as you study share your notes with friends eBooks are downloaded to your computer and accessible either offline through the Bookshelf (available as a free download), available online and also via the iPad and Android apps. Upon purchase, you'll gain instant access to this eBook. Time limit The eBooks products do not have an expiry date. You will continue to access your digital ebook products whilst you have your Bookshelf installed. |
| data science masters usc: Advanced Mechanical Design Wen Zhe Chen, Pin Qiang Dai, Yong Lu Chen, Qian Ting Wang, Zheng Yi Jiang, 2012-02-27 Selected, peer reviewed papers from the 3rd international Conference on Manufacturing Science and Engineering (ICMSE 2012), March 27-29, 2012, Xiamen, China |
| data science masters usc: Communicating at Work Ronald B. Adler, Ronald Brian Adler, Jeanne Marquardt Elmhorst, Kristen Lucas, 2012-10 The 11th edition of Communicating at Work enhances the strategic approach, real-world practicality, and reader-friendly voice that have made this text the market leader for three decades. On every page, students learn how to communicate in ways that enhance their own career success and help their organization operate effectively. This edition retains the hallmark features that have been praised by faculty and students--a strong emphasis on ethical communication and cultural diversity, discussions of evolving communication technologies, and self-assessment tools--while incorporating important updates and ground-breaking digital teaching and learning tools to help students better connect to the course material and apply it to real world business situations. |
| data science masters usc: The Last Great Necessity David Charles Sloane, 1991 The Last Great Necessity is a quite wonderful, and often surprising, portrait of American popular culture in action. As David Charles Sloane traces the history of modern cemeteries he meets all the ambivalences and coping strategies Americans have used when they have been forced by nature to confront the meanings of their lives. - From Sam Bass Warner, Jr., Boston University. |
| data science masters usc: Data Augmented Design Ying Long, Enjia Zhang, 2020-08-13 This book offers an essential introduction to a new urban planning and design methodology called Data Augmented Design (DAD) and its evolution and progresses, highlighting data driven methods, urban planning and design applications and related theories. The authors draw on many kinds of data, including big, open, and conventional data, and discuss cutting-edge technologies that illustrate DAD as a future oriented design framework in terms of its focus on multi-data, multi-method, multi-stage and multi-scale sustainable urban planning. In four sections and ten chapters, the book presents case studies to address the core concepts of DAD, the first type of applications of DAD that emerged in redevelopment-oriented planning and design, the second type committed to the planning and design for urban expansion, and the future-oriented applications of DAD to advance sustainable technologies and the future structural form of the built environment. The book is geared towards a broad readership, ranging from researchers and students of urban planning, urban design, urban geography, urban economics, and urban sociology, to practitioners in the areas of urban planning and design. |
| data science masters usc: Challenges for Games Designers Brenda Brathwaite, 2008-08-21 Welcome to a book written to challenge you, improve your brainstorming abilities, and sharpen your game design skills! Challenges for Game Designers: Non-Digital Exercises for Video Game Designers is filled with enjoyable, interesting, and challenging exercises to help you become a better video game designer, whether you are a professional or aspire to be. Each chapter covers a different topic important to game designers, and was taken from actual industry experience. After a brief overview of the topic, there are five challenges that each take less than two hours and allow you to apply the material, explore the topic, and expand your knowledge in that area. Each chapter also includes 10 non-digital shorts to further hone your skills. None of the challenges in the book require any programming or a computer, but many of the topics feature challenges that can be made into fully functioning games. The book is useful for professional designers, aspiring designers, and instructors who teach game design courses, and the challenges are great for both practice and homework assignments. The book can be worked through chapter by chapter, or you can skip around and do only the challenges that interest you. As with anything else, making great games takes practice and Challenges for Game Designers provides you with a collection of fun, thought-provoking, and of course, challenging activities that will help you hone vital skills and become the best game designer you can be. |
| data science masters usc: Right College, Right Price Frank Palmasani, 2013 Describes how the Financial Fit program can help families determine how much college will really cost beyond the sticker price and factor cost into the college search, and explains how to maximize financial aid benefits. |
| data science masters usc: Hands-On Deep Learning with R Michael Pawlus, Rodger Devine, 2020-04-24 Explore and implement deep learning to solve various real-world problems using modern R libraries such as TensorFlow, MXNet, H2O, and Deepnet Key FeaturesUnderstand deep learning algorithms and architectures using R and determine which algorithm is best suited for a specific problemImprove models using parameter tuning, feature engineering, and ensemblingApply advanced neural network models such as deep autoencoders and generative adversarial networks (GANs) across different domainsBook Description Deep learning enables efficient and accurate learning from a massive amount of data. This book will help you overcome a number of challenges using various deep learning algorithms and architectures with R programming. This book starts with a brief overview of machine learning and deep learning and how to build your first neural network. You’ll understand the architecture of various deep learning algorithms and their applicable fields, learn how to build deep learning models, optimize hyperparameters, and evaluate model performance. Various deep learning applications in image processing, natural language processing (NLP), recommendation systems, and predictive analytics will also be covered. Later chapters will show you how to tackle recognition problems such as image recognition and signal detection, programmatically summarize documents, conduct topic modeling, and forecast stock market prices. Toward the end of the book, you will learn the common applications of GANs and how to build a face generation model using them. Finally, you’ll get to grips with using reinforcement learning and deep reinforcement learning to solve various real-world problems. By the end of this deep learning book, you will be able to build and deploy your own deep learning applications using appropriate frameworks and algorithms. What you will learnDesign a feedforward neural network to see how the activation function computes an outputCreate an image recognition model using convolutional neural networks (CNNs)Prepare data, decide hidden layers and neurons and train your model with the backpropagation algorithmApply text cleaning techniques to remove uninformative text using NLPBuild, train, and evaluate a GAN model for face generationUnderstand the concept and implementation of reinforcement learning in RWho this book is for This book is for data scientists, machine learning engineers, and deep learning developers who are familiar with machine learning and are looking to enhance their knowledge of deep learning using practical examples. Anyone interested in increasing the efficiency of their machine learning applications and exploring various options in R will also find this book useful. Basic knowledge of machine learning techniques and working knowledge of the R programming language is expected. |
Data Science Program - University of Southern California
We offer several master's degree programs that enable students to acquire data science skills in the context of a particular discipline. These programs are designed to gently introduce students …
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The USC Marshall MSBA program is a data science STEM program with a business lens. It is one of the longest running MSBA programs in the nation, and top ranking in the world. The program …
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Data Science Program - University of Southern California
We offer a comprehensive Master of Science in Applied Data Science program that enable students to learn about a range of topics in machine learning, distributed data systems, and the …
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The USC Marshall MSBA program is a data science STEM program with a business lens. It is one of the longest running MSBA programs in the nation, and top ranking in the world. The program …
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The USC Viterbi School of Engineering Master of Science in Applied Data Science will train students as data scientists. This degree provides students with the knowledge and skill to …
Program Learning Objectives - University of Southern California
USC students enrolled in the USC Viterbi School of Engineering Master of Science in Communication Data Science program will learn a range of data science skills such as …
Introducing the MS in Economics and Data Science at USC
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The Master of Science in Economics and Data Science combines core economic theory and econometric —at a relatively high level for a master’s program with foundational instruction in …
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This information is for engineering/computer science Master of Science programs offered by the USC Viterbi School of Engineering requiring the successful completion of a minimum of 32 …
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The USC Marshall MSBA program is a data science STEM program with a business lens. It is one of the longest running MSBA programs in the nation, and top ranking in the world.
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USC students enrolled in the USC Viterbi School of Engineering Master of Science in Healthcare Data Science program will learn a range of data science skills such as developing scalable …
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Data Science Mathematics Preventative Medicine Psychology Public Planning and Development Social Work Sociology . USC MATH 6 *The following courses may not be used as electives for …
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1. Develop sufficient proficiency in Big Data frameworks to write software capable of automatically extracting information from data including its text and metadata and language. 2. Develop …
MASTER OF SCIENCE IN ENVIRONMENTAL DATA SCIENCE
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Master’s Program Handbook - University of Southern California
Our faculty works with the National Science Foundation, the Integrated Media Systems Center (based at USC) and private companies, to stay at the forefront of innovation in software, control …
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The M.S. in Spatial Economics and Data Analysis (SEDA) combines the curriculum of a n MA in Economics with a core MS in Data Science curriculum, linked by spatial sciences curriculum. In …
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Students also choose USC because of its leadership in ISE research. Our faculty works with the National Science Foundation, the Integrated Media Systems Center (based at USC) and private …
Master’s Program Handbook - University of Southern California
Our faculty works with the National Science Foundation, the Integrated Media Systems Center (based at USC) and private companies, to stay at the forefront of innovation in software, control …
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learning and data science. Upon completion of the USC Master of Science in Electrical and Computer Engineering (Machine Learning and Data Science) program, students will be able to …
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Twenty One units must be at 500 level or above. Graduate …
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SSCI 581 (35691D and 35892D), Concepts for Spatial Thinking
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Translational Genomics - University of Southern California
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Upon completion of the USC Viterbi School of Engineering Master of Science in Biomedical Data Analytics, students will: • demonstrate advanced understanding of subject matter linking human …
Program Learning Objectives - University of Southern California
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UNMANNED AERIAL SYSTEMS FOR SURVEYING AND …
COST COMPARISON OF UAS VERSUS TRADITIONAL METHODS OF DATA ACQUISITION by Bryan Phillip Fitzpatrick A Thesis Presented to the FACULTY OF THE USC GRADUATE SCHOOL …
CSCI 499: Introduction to Human-Computer Interaction
Page 3 of 9 Optional Readings and Supplementary Materials • Rocket Surgery Made Easy by S. Krug, 2010. Available through USC Libraries. • Simple and Usable: Web, Mobile, and Interaction …
Master of Science in Product Development Engineering
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Program Learning Objectives - viterbischool.usc.edu
Master of Science in Astronautical Engineering Program Learning Objectives The purpose of the USC Viterbi School of Engineering Master of Science Program in Astronautical Engineering is to …
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