Python Data Science Handbook

With contributions by 42 of the best political scientists worldwide, A New Handbook of Political Science analyzes the progress made in political science over the past twenty years in the context of hi

This book is a customized version in Taiwan, and the content is extracted from Chapters 1 to 15 of the book "Introduction to Python Programming and Data Structures, Global Edition, 3rd edition".-- --For introductory courses in Python Programming.A fundamentals first approach to programming helps students create efficient, elegant code.Introduction to Python Programming and Data Structures introduces students to basic programming concepts using a fundamentals-first approach that prepares students to learn object-oriented programming and advanced Python programming. This approach presents programming concepts and techniques that include control statements, loops, functions, and arrays before designing custom classes. Students learn basic logic and programming concepts prior to moving into object-oriented and GUI programming. The content incorporates a wide variety of problems with various levels of difficulty and covers many application areas to engage and motivate students.For a list of

Optimization techniques are at the core of data science, including data analysis and machine learning. An understanding of basic optimization techniques and their fundamental properties provides important grounding for students, researchers, and practitioners in these areas. This text covers the fundamentals of optimization algorithms in a compact, self-contained way, focusing on the techniques most relevant to data science. An introductory chapter demonstrates that many standard problems in data science can be formulated as optimization problems. Next, many fundamental methods in optimization are described and analyzed, including: gradient and accelerated gradient methods for unconstrained optimization of smooth (especially convex) functions; the stochastic gradient method, a workhorse algorithm in machine learning; the coordinate descent approach; several key algorithms for constrained optimization problems; algorithms for minimizing nonsmooth functions arising in data science; found

This textbook provides future data analysts with the tools, methods, and skills needed to answer data-focused, real-life questions; to carry out data analysis; and to visualize and interpret results to support better decisions in business, economics, and public policy. Data wrangling and exploration, regression analysis, machine learning, and causal analysis are comprehensively covered, as well as when, why, and how the methods work, and how they relate to each other. As the most effective way to communicate data analysis, running case studies play a central role in this textbook. Each case starts with an industry-relevant question and answers it by using real-world data and applying the tools and methods covered in the textbook. Learning is then consolidated by 360 practice questions and 120 data exercises. Extensive online resources, including raw and cleaned data and codes for all analysis in Stata, R, and Python, can be found at www.gabors-data-analysis.com.

This textbook provides future data analysts with the tools, methods, and skills needed to answer data-focused, real-life questions; to carry out data analysis; and to visualize and interpret results to support better decisions in business, economics, and public policy. Data wrangling and exploration, regression analysis, machine learning, and causal analysis are comprehensively covered, as well as when, why, and how the methods work, and how they relate to each other. As the most effective way to communicate data analysis, running case studies play a central role in this textbook. Each case starts with an industry-relevant question and answers it by using real-world data and applying the tools and methods covered in the textbook. Learning is then consolidated by 360 practice questions and 120 data exercises. Extensive online resources, including raw and cleaned data and codes for all analysis in Stata, R, and Python, can be found at www.gabors-data-analysis.com.

Machine Learning and Data Science in the Oil and Gas Industry explains how machine learning can be specifically tailored to oil and gas use cases. Petroleum engineers will learn when to use machine learning, how it is already used in oil and gas operations, and how to manage the data stream moving forward. Practical in its approach, the book explains all aspects of a data science or machine learning project, including the managerial parts of it that are so often the cause for failure.Several real-life case studies round out the book with topics such as predictive maintenance, soft sensing, and forecasting. Viewed as a guide book, this manual will lead a practitioner through the journey of a data science project in the oil and gas industry circumventing the pitfalls and articulating the business value.

Enhance your data science programming and analysis with the Wolfram programming language and Mathematica, an applied mathematical tools suite. The book introduces you to the Wolfram programming langua

Python programmers will improve their computer science skills with these useful one-liners.Python One-Liners will teach you how to read and write one-liners: concise statements of useful functionality

Learn about the state-of-the-art at the interface between information theory and data science with this first unified treatment of the subject. Written by leading experts in a clear, tutorial style, and using consistent notation and definitions throughout, it shows how information-theoretic methods are being used in data acquisition, data representation, data analysis, and statistics and machine learning. Coverage is broad, with chapters on signal acquisition, data compression, compressive sensing, data communication, representation learning, emerging topics in statistics, and much more. Each chapter includes a topic overview, definition of the key problems, emerging and open problems, and an extensive reference list, allowing readers to develop in-depth knowledge and understanding. Providing a thorough survey of the current research area and cutting-edge trends, this is essential reading for graduate students and researchers working in information theory, signal processing, machine le

Avoid data blunders and create truly useful visualizations Avoiding Data Pitfalls is a reputation-saving handbook for those who work with data, designed to help you avoid the all-too-common blunders t

The Handbook of U.S. Labor Statistics: Employment, Earnings, Prices, Productivity, and Other Labor Data continues and enhances the Bureau of Labor Statistics's (BLS) discontinued publication, Labo

Image Analysis, Classification and Change Detection in Remote Sensing: With Algorithms for Python, Fourth Edition, is focused on the development and implementation of statistically motivated, data-dri

This book constitutes the post-conference proceedings of the 4th International Conference on Machine Learning, Optimization, and Data Science, LOD 2018, held in Volterra, Italy, in September 2018.The

The fast and easy way to learn Python programming and statisticsPython is a general-purpose programming language created in the late 1980s—and named after Monty Python—that's used by thousands of peop

Gain the R programming language fundamentals for doing the applied statistics useful for data exploration and analysis in data science and data mining. This book covers topics ranging from R syntax ba

The Cambridge Handbook of International Prevention Science offers a comprehensive global overview on prevention science with the most up-to-date research from around the world. Over 100 scholars from 27 different countries (including Australia, Bhutan, Botswana, India, Israel, Mexico, Singapore, South Korea, Spain and Thailand) contributed to this volume, which covers a wide range of topics important to prevention science. It includes major sections on the foundations of prevention as well as examples of new initiatives in the field, detailing current prevention efforts across the five continents. A unique and innovative volume, The Cambridge Handbook of International Prevention Science is a valuable resource for established scholars, early professionals, students, practitioners and policy-makers.

"A great, action-oriented book for novice data analysts. If you have no background in quantitative social science, Fogarty's book gives you a toolbox for starting statistical analysis and develop

"A great, action-oriented book for novice data analysts. If you have no background in quantitative social science, Fogarty's book gives you a toolbox for starting statistical analysis and develop

A new volume in the Handbook of Sports Medicine and Science series from the International Olympic Committee, this volume Canoeing provides an accessible and comprehensive summary of the topic. Pr

Learn the basics of Data Science through an easy to understand conceptual framework and immediately practice using RapidMiner platform. Whether you are brand new to data science or working on your ten

Transportation Science explores the fundamental principle of analyzing different types of transportation-related data using methodologies such as the data fusion model, the big data mining approach, c

Understand the fundamental factors of data storage system performance and master an essential analytical skill using block trace via applications such as MATLAB and Python tools. You will increase you

This book addresses the current status, challenges and future directions of data-driven materials discovery and design. It presents the analysis and learning from data as a key theme in many science a

Data Science for Business and Decision Making covers both statistics and operations research while most competing textbooks focus on one or the other. As a result, the book more clearly defines the pr

Panel Data Econometrics with R provides a tutorial for using R in the field of panel data econometrics. Illustrated throughout with examples in econometrics, political science, agriculture and epidemi

This book offers examples of how data science, big data, analytics, and cloud technology can be used in healthcare to significantly improve a hospital’s IT Energy Efficiency along with information on

This book presents the outcomes of the 3rd IEEE/ACIS International Conference on Big Data, Cloud Computing, Data Science & Engineering (BCD 2018), which was held on July 10–12, 2018 in Kanazawa. The aim of the conference was to bring together researchers and scientists, businesspeople and entrepreneurs, teachers, engineers, computer users, and students to discuss the various fields of computer science, to share their experiences, and to exchange new ideas and information in a meaningful way. All aspects (theory, applications and tools) of computer and information science, the practical challenges encountered along the way, and the solutions adopted to solve them are all explored here.The conference organizers selected the best papers from among those accepted for presentation. The papers were chosen on the basis of review scores submitted by members of the program committee and subsequently underwent further rigorous review. Following this second round of review, 13 of the conferen

With a focus on science in the ancient societies of Greece and Rome, including glimpses into Egypt, Mesopotamia, India and China, The Oxford Handbook of Science and Medicine in the Classical World off

Deal with data, build up financial formulas in code from scratch, and evaluate and think about money in your day-to-day life. This book is about Python and personal finance and how you can effectively

The Handbook of U.S. Labor Statistics: Employment, Earnings, Prices, Productivity, and Other Labor Data continues and enhances the Bureau of Labor Statistics's (BLS) discontinued publication, Labo

The Volume of “Advances in Machine Learning and Data Science - Recent Achievements and Research Directives” constitutes the proceedings of First International Conference on Latest Advances in Machine

This textbook for graduate students in statistics, data science, and public health deals with the practical challenges that come with big, complex, and dynamic data. It presents a scientific roadmap t

Discover the art and science of solving artificial intelligence problems with Python using optimization modeling. This book covers the practical creation and analysis of mathematical algebraic models

Data Stewardship for Open Science: Implementing FAIR Principles has been written with the intention of making scientists, funders, and innovators in all disciplines and stages of their professional ac

Data Stewardship for Open Science: Implementing FAIR Principles has been written with the intention of making scientists, funders, and innovators in all disciplines and stages of their professional ac

This edited book focuses on the latest developments in classification, statistical learning, data analysis and related areas of data science, including statistical analysis of large datasets, big data

Interpretive political science focuses on the meanings that shape actions and institutions, and the ways in which they do so. This Handbook explores the implications of interpretive theory for the stu

Data science is the most exciting skill you can master. Data has dramatically changed how our world works. From entertainment to politics, from technology to advertising and from science to the busine

A fully updated tutorial on the basics of the Python programming language for science studentsPython is a computer programming language that is rapidly gaining popularity throughout the sciences. This

A fully updated tutorial on the basics of the Python programming language for science studentsPython is a computer programming language that is rapidly gaining popularity throughout the sciences. This