Download or read book Modern Data Science with R written by Benjamin S. Baumer and published by CRC Press. This book was released on 2021-03-31 with total page 830 pages. Available in PDF, EPUB and Kindle. Book excerpt: From a review of the first edition: "Modern Data Science with R... is rich with examples and is guided by a strong narrative voice. What’s more, it presents an organizing framework that makes a convincing argument that data science is a course distinct from applied statistics" (The American Statistician). Modern Data Science with R is a comprehensive data science textbook for undergraduates that incorporates statistical and computational thinking to solve real-world data problems. Rather than focus exclusively on case studies or programming syntax, this book illustrates how statistical programming in the state-of-the-art R/RStudio computing environment can be leveraged to extract meaningful information from a variety of data in the service of addressing compelling questions. The second edition is updated to reflect the growing influence of the tidyverse set of packages. All code in the book has been revised and styled to be more readable and easier to understand. New functionality from packages like sf, purrr, tidymodels, and tidytext is now integrated into the text. All chapters have been revised, and several have been split, re-organized, or re-imagined to meet the shifting landscape of best practice.
Download or read book Understanding Analysis written by Stephen Abbott and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 269 pages. Available in PDF, EPUB and Kindle. Book excerpt: This elementary presentation exposes readers to both the process of rigor and the rewards inherent in taking an axiomatic approach to the study of functions of a real variable. The aim is to challenge and improve mathematical intuition rather than to verify it. The philosophy of this book is to focus attention on questions which give analysis its inherent fascination. Each chapter begins with the discussion of some motivating examples and concludes with a series of questions.
Download or read book Protective Relaying written by J. Lewis Blackburn and published by CRC Press. This book was released on 2014-02-11 with total page 678 pages. Available in PDF, EPUB and Kindle. Book excerpt: For many years, Protective Relaying: Principles and Applications has been the go-to text for gaining proficiency in the technological fundamentals of power system protection. Continuing in the bestselling tradition of the previous editions by the late J. Lewis Blackburn, the Fourth Edition retains the core concepts at the heart of power system anal
Download or read book Understanding Machine Learning written by Shai Shalev-Shwartz and published by Cambridge University Press. This book was released on 2014-05-19 with total page 415 pages. Available in PDF, EPUB and Kindle. Book excerpt: Introduces machine learning and its algorithmic paradigms, explaining the principles behind automated learning approaches and the considerations underlying their usage.
Download or read book Introduction to Applied Linear Algebra written by Stephen Boyd and published by Cambridge University Press. This book was released on 2018-06-07 with total page 477 pages. Available in PDF, EPUB and Kindle. Book excerpt: A groundbreaking introduction to vectors, matrices, and least squares for engineering applications, offering a wealth of practical examples.
Download or read book The Elements of Statistical Learning written by Trevor Hastie and published by Springer Science & Business Media. This book was released on 2013-11-11 with total page 545 pages. Available in PDF, EPUB and Kindle. Book excerpt: During the past decade there has been an explosion in computation and information technology. With it have come vast amounts of data in a variety of fields such as medicine, biology, finance, and marketing. The challenge of understanding these data has led to the development of new tools in the field of statistics, and spawned new areas such as data mining, machine learning, and bioinformatics. Many of these tools have common underpinnings but are often expressed with different terminology. This book describes the important ideas in these areas in a common conceptual framework. While the approach is statistical, the emphasis is on concepts rather than mathematics. Many examples are given, with a liberal use of color graphics. It should be a valuable resource for statisticians and anyone interested in data mining in science or industry. The book’s coverage is broad, from supervised learning (prediction) to unsupervised learning. The many topics include neural networks, support vector machines, classification trees and boosting---the first comprehensive treatment of this topic in any book. This major new edition features many topics not covered in the original, including graphical models, random forests, ensemble methods, least angle regression & path algorithms for the lasso, non-negative matrix factorization, and spectral clustering. There is also a chapter on methods for “wide” data (p bigger than n), including multiple testing and false discovery rates. Trevor Hastie, Robert Tibshirani, and Jerome Friedman are professors of statistics at Stanford University. They are prominent researchers in this area: Hastie and Tibshirani developed generalized additive models and wrote a popular book of that title. Hastie co-developed much of the statistical modeling software and environment in R/S-PLUS and invented principal curves and surfaces. Tibshirani proposed the lasso and is co-author of the very successful An Introduction to the Bootstrap. Friedman is the co-inventor of many data-mining tools including CART, MARS, projection pursuit and gradient boosting.
Download or read book Fundamentals of Machine Learning for Predictive Data Analytics second edition written by John D. Kelleher and published by MIT Press. This book was released on 2020-10-20 with total page 853 pages. Available in PDF, EPUB and Kindle. Book excerpt: The second edition of a comprehensive introduction to machine learning approaches used in predictive data analytics, covering both theory and practice. Machine learning is often used to build predictive models by extracting patterns from large datasets. These models are used in predictive data analytics applications including price prediction, risk assessment, predicting customer behavior, and document classification. This introductory textbook offers a detailed and focused treatment of the most important machine learning approaches used in predictive data analytics, covering both theoretical concepts and practical applications. Technical and mathematical material is augmented with explanatory worked examples, and case studies illustrate the application of these models in the broader business context. This second edition covers recent developments in machine learning, especially in a new chapter on deep learning, and two new chapters that go beyond predictive analytics to cover unsupervised learning and reinforcement learning.
Download or read book Statistics written by Robin H. Lock and published by John Wiley & Sons. This book was released on 2020-10-13 with total page 866 pages. Available in PDF, EPUB and Kindle. Book excerpt: Statistics: Unlocking the Power of Data, 3rd Edition is designed for an introductory statistics course focusing on data analysis with real-world applications. Students use simulation methods to effectively collect, analyze, and interpret data to draw conclusions. Randomization and bootstrap interval methods introduce the fundamentals of statistical inference, bringing concepts to life through authentically relevant examples. More traditional methods like t-tests, chi-square tests, etc. are introduced after students have developed a strong intuitive understanding of inference through randomization methods. While any popular statistical software package may be used, the authors have created StatKey to perform simulations using data sets and examples from the text. A variety of videos, activities, and a modular chapter on probability are adaptable to many classroom formats and approaches.
Download or read book Fundamentals of Physics Chapters 1 to 22 written by David Halliday and published by Wiley. This book was released on 1993-09-13 with total page 752 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Intro Stats written by Richard D. De Veaux and published by . This book was released on 2005-03 with total page 736 pages. Available in PDF, EPUB and Kindle. Book excerpt: CD-ROM contains ActivStats multimedia learning support program, data for marked exercises and two additional chapters covering analysis of variance and multiple regression.
Download or read book Instructor s Manual for Food Analysis written by S. Suzanne Nielsen and published by Springer. This book was released on 2012-12-06 with total page 145 pages. Available in PDF, EPUB and Kindle. Book excerpt: The first and second editions of Food Analysis were widely adopted for teaching the subject of Food Analysis and were found useful in the food industry. The third edition has been revised and updated for the same intended use, and is being published with an accompanying laboratory manual. Food Analysis, Third Edition, has a general information section that includes governmental regulations related to food analysis, sampling, and data handling as background chapters. The major sections of the book contain chapters on compositional analysis and on chemical properties and characteristics of foods. A new chapter is included on agricultural biotechnology (GMO) methods of analysis. Large sections on spectroscopy, chromatography, and physical properties are included. All topics covered contain information on the basic principles, procedures, advantages, limitation, and applications. This book is ideal for undergraduate courses in food analysis and also is an invaluable reference to professions in the food industry.
Download or read book Instructor s Manual to Accompany Microcomputer Use Word Processors Spreadsheets and Data Bases with Accompanying MicroUSE Software written by Teresa Alberte-Hallam and published by Academic Press. This book was released on 2014-06-28 with total page 75 pages. Available in PDF, EPUB and Kindle. Book excerpt: Instructor's Manual to accompany Microcomputer Use Word Processors, Spreadsheets, and Data Bases with Accompanying MicroUSE Software focuses on the concepts and functions common to most commercial word processing, electronic spreadsheet, database management software, and other microcomputer software. Computer engineers will find the book useful.
Download or read book How English Works written by Ann Raimes and published by Cambridge University Press. This book was released on 1998-07-13 with total page 420 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book uses readings from newspapers, works of non-fiction, and college textbooks to illustrate the use of target structures. The Student's Book provides clear presentations of the basic principles of 27 important areas of English grammar, through a wide variety of exercises and tasks for writing and editing. It engages students with topics that range from artificial intelligence and laptop computers to the environment and economics. This important grammar text provides a real-world context that allows students to see how the English language really "works."
Download or read book Instructor s Manual for Understanding Fiber Optics Fifth Edition written by Jeff Hecht and published by Jeff Hecht. This book was released on 2022-08-02 with total page 111 pages. Available in PDF, EPUB and Kindle. Book excerpt: An instruction manual for use with the fifth edition of Understanding Fiber Optics by Jeff Hecht. This book includes an overview for instructors, answers to quizzes and "questions to think about" published in the book, worked-out solutions to selected problems with equations, and additional material to supplement the book. This is the original manual prepared and published in 2006 along with the fifth edition of Understanding Fiber Optics, with only minimal updates.
Download or read book Introduction to Statistics and Data Analysis written by Roxy Peck and published by . This book was released on 2015-03-27 with total page 844 pages. Available in PDF, EPUB and Kindle. Book excerpt: INTRODUCTION TO STATISTICS AND DATA ANALYSIS introduces you to the study of statistics and data analysis by using real data and attention-grabbing examples. The authors guide you through an intuition-based learning process that stresses interpretation and communication of statistical information. Simple notation--including frequent substitution of words for symbols--helps you grasp concepts and cement your comprehension. You'll also find coverage of most major technologies as a problem-solving tool, plus hands-on activities in each chapter that allow you to practice statistics firsthand.
Download or read book Instructor s Solutions Manual written by Allen R. Angel and published by Prentice Hall. This book was released on 2003-02 with total page 580 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book The Data Science Design Manual written by Steven S. Skiena and published by Springer. This book was released on 2017-07-01 with total page 456 pages. Available in PDF, EPUB and Kindle. Book excerpt: This engaging and clearly written textbook/reference provides a must-have introduction to the rapidly emerging interdisciplinary field of data science. It focuses on the principles fundamental to becoming a good data scientist and the key skills needed to build systems for collecting, analyzing, and interpreting data. The Data Science Design Manual is a source of practical insights that highlights what really matters in analyzing data, and provides an intuitive understanding of how these core concepts can be used. The book does not emphasize any particular programming language or suite of data-analysis tools, focusing instead on high-level discussion of important design principles. This easy-to-read text ideally serves the needs of undergraduate and early graduate students embarking on an “Introduction to Data Science” course. It reveals how this discipline sits at the intersection of statistics, computer science, and machine learning, with a distinct heft and character of its own. Practitioners in these and related fields will find this book perfect for self-study as well. Additional learning tools: Contains “War Stories,” offering perspectives on how data science applies in the real world Includes “Homework Problems,” providing a wide range of exercises and projects for self-study Provides a complete set of lecture slides and online video lectures at www.data-manual.com Provides “Take-Home Lessons,” emphasizing the big-picture concepts to learn from each chapter Recommends exciting “Kaggle Challenges” from the online platform Kaggle Highlights “False Starts,” revealing the subtle reasons why certain approaches fail Offers examples taken from the data science television show “The Quant Shop” (www.quant-shop.com)