Data Science Applications Using Python And R

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Data Science Using Python And R

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Author : Chantal D. Larose
language : en
Publisher: John Wiley & Sons
Release Date : 2019-03-20

Data Science Using Python And R written by Chantal D. Larose and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-03-20 with Computers categories.

Learn data science by doing data science! Data Science Using Python and R will get you plugged into the world’s two most widespread open-source platforms for data science: Python and R. Data science is hot. Bloomberg called data scientist “the hottest job in America.” Python and R are the top two open-source data science tools in the world. In Data Science Using Python and R, you will learn step-by-step how to produce hands-on solutions to real-world business problems, using state-of-the-art techniques. Data Science Using Python and R is written for the general reader with no previous analytics or programming experience. An entire chapter is dedicated to learning the basics of Python and R. Then, each chapter presents step-by-step instructions and walkthroughs for solving data science problems using Python and R. Those with analytics experience will appreciate having a one-stop shop for learning how to do data science using Python and R. Topics covered include data preparation, exploratory data analysis, preparing to model the data, decision trees, model evaluation, misclassification costs, naïve Bayes classification, neural networks, clustering, regression modeling, dimension reduction, and association rules mining. Further, exciting new topics such as random forests and general linear models are also included. The book emphasizes data-driven error costs to enhance profitability, which avoids the common pitfalls that may cost a company millions of dollars. Data Science Using Python and R provides exercises at the end of every chapter, totaling over 500 exercises in the book. Readers will therefore have plenty of opportunity to test their newfound data science skills and expertise. In the Hands-on Analysis exercises, readers are challenged to solve interesting business problems using real-world data sets.

Data Science Applications Using Python And R

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Author : Jeffrey Strickland
language : en
Publisher:
Release Date : 2020-08-23

Data Science Applications Using Python And R written by Jeffrey Strickland and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-08-23 with categories.

Data Science Applications using Python and R is the second book in a series that began in 2018. This volume is dedicated to text analytics and natural language processing. Using real data, the author leads the reader through the analysis of Tweet sentiment analysis, banking product-group complaint analysis, presidential debate analysis, and more. The book covers text mining, natural language processing (NLP), vectorizing text data, discrete classifiers, bag-of-words (BOW) models, sentiment analysis, and Latent Dirichlet Allocation (LDA). The book offers complete Python and R code with detail explanations. It is designed for use with Jupyter Notebook and R Studio. It also includes notes on Python and R markdown and features full color graphics and text on heavy paper. All data sets used in the book are downloadable from GitHub. Some data can also be customized and download ed from the Federal Consumer Complaint Data Catalog. Finally, each chapter contains practice exercises.

Beginning C 7 Programming With Visual Studio 2017

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Author : Benjamin Perkins
language : en
Publisher: John Wiley & Sons
Release Date : 2018-04-17

Beginning C 7 Programming With Visual Studio 2017 written by Benjamin Perkins and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-04-17 with Computers categories.

Easily get started programming using the ultra-versatile C# 7 and Visual Studio 2017 Beginning C# 7 Programming with Visual Studio 2017 is the beginner’s ultimate guide to the world’s most popular programming language. Whether you’re new to programming entirely, or just new to C#, there has never been a better time to get started. The new C# 7 and Visual Studio 2017 updates feature a number of new tools and features that streamline the workflow, simplify the code, and make it easier than ever to build high-quality apps. This book walks you through everything you need to know, starting from the very basics, to have you programming in no time. You’ll learn about variables, flow control, and object oriented programming, then move into Web and Windows programming as well as databases and XML. The companion website provides downloadable code examples, and practical Try It Out sections provide explicit, step-by-step instructions for writing your own useful, customizable code. C# 7 can be used to build Windows applications, program Windows 10, and write Web apps when used alongside ASP.NET. With programming skills becoming de rigueur in fields far beyond the tech world, C# 7 is a great place to start building versatile, helpful skills. This book gets you started quickly and easily with instruction from a master-team of C# programmers. Learn how to program using the world’s leading programming language Build smarter, faster apps using the latest features in C# 7 and Visual Studio 2017 Find and fix bugs sooner, saving headaches down the line Integrate with all .NET Core, Azure applications, cloud services, Docker containers, and more The world of programming can seem intimidating to a beginner, and the prospect of learning a whole new “language” can seem daunting. Beginning C# 7 Programming with Visual Studio 2017 demystifies the process and shows you how to bring your ideas to life.

Developing Analytic Talent

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Author : Vincent Granville
language : en
Publisher: John Wiley & Sons
Release Date : 2014-04-07

Developing Analytic Talent written by Vincent Granville and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-04-07 with Computers categories.

Learn what it takes to succeed in the the most in-demand tech job Harvard Business Review calls it the sexiest tech job of the 21st century. Data scientists are in demand, and this unique book shows you exactly what employers want and the skill set that separates the quality data scientist from other talented IT professionals. Data science involves extracting, creating, and processing data to turn it into business value. With over 15 years of big data, predictive modeling, and business analytics experience, author Vincent Granville is no stranger to data science. In this one-of-a-kind guide, he provides insight into the essential data science skills, such as statistics and visualization techniques, and covers everything from analytical recipes and data science tricks to common job interview questions, sample resumes, and source code. The applications are endless and varied: automatically detecting spam and plagiarism, optimizing bid prices in keyword advertising, identifying new molecules to fight cancer, assessing the risk of meteorite impact. Complete with case studies, this book is a must, whether you're looking to become a data scientist or to hire one. Explains the finer points of data science, the required skills, and how to acquire them, including analytical recipes, standard rules, source code, and a dictionary of terms Shows what companies are looking for and how the growing importance of big data has increased the demand for data scientists Features job interview questions, sample resumes, salary surveys, and examples of job ads Case studies explore how data science is used on Wall Street, in botnet detection, for online advertising, and in many other business-critical situations Developing Analytic Talent: Becoming a Data Scientist is essential reading for those aspiring to this hot career choice and for employers seeking the best candidates.

Professional Visual Studio 2017

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Author : Bruce Johnson
language : en
Publisher: John Wiley & Sons
Release Date : 2017-11-06

Professional Visual Studio 2017 written by Bruce Johnson and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-11-06 with Computers categories.

Skip the basics and delve right into Visual Studio 2017 advanced features and tools Professional Visual Studio 2017 is the industry-favorite guide to getting the most out of Microsoft's primary programming technology. From touring the new UI to exploiting advanced functionality, this book is designed to help professional developers become more productive. A unique IDE-centric approach provides a clear path through the typical workflow while exploring the nooks and crannies that can make your job easier. Visual Studio 2017 includes a host of features aimed at improving developer productivity and UI, and this book covers them all with clear explanation, new figures, and expert insight. Whether you're new to VS or just upgrading, this all-inclusive guide is an essential resource to keep within arm's reach. Visual Studio 2017 fixes the crucial issues that kept professionals from adopting VS 2015, and includes new features and tools that streamline the developer's job. This book provides the straightforward answers you need so you can get up to speed quickly and get back to work. Master the core functionality of Visual Studio 2017 Dig into the tools that make writing code easier Tailor the environment to your workflow, not the other way around Work your way through configuration, debugging, building, deployment, customizing, and more Microsoft is changing their release cadence—it's only been about two years since the last release—so developers need to quickly get a handle on new tools and features if they hope to remain productive. The 2017 release is designed specifically to help you get more done, in less time, with greater accuracy and attention to detail. If you're ready to get acquainted, Professional Visual Studio 2017 is your ideal guide.

Python For Programmers

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Author : Paul Deitel
language : en
Publisher: Prentice Hall
Release Date : 2019-03-15

Python For Programmers written by Paul Deitel and has been published by Prentice Hall this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-03-15 with Computers categories.

The professional programmer’s Deitel® guide to Python® with introductory artificial intelligence case studies Written for programmers with a background in another high-level language, Python for Programmers uses hands-on instruction to teach today’s most compelling, leading-edge computing technologies and programming in Python–one of the world’s most popular and fastest-growing languages. Please read the Table of Contents diagram inside the front cover and the Preface for more details. In the context of 500+, real-world examples ranging from individual snippets to 40 large scripts and full implementation case studies, you’ll use the interactive IPython interpreter with code in Jupyter Notebooks to quickly master the latest Python coding idioms. After covering Python Chapters 1-5 and a few key parts of Chapters 6-7, you’ll be able to handle significant portions of the hands-on introductory AI case studies in Chapters 11-16, which are loaded with cool, powerful, contemporary examples. These include natural language processing, data mining Twitter® for sentiment analysis, cognitive computing with IBM® WatsonTM, supervised machine learning with classification and regression, unsupervised machine learning with clustering, computer vision through deep learning and convolutional neural networks, deep learning with recurrent neural networks, big data with Hadoop®, SparkTM and NoSQL databases, the Internet of Things and more. You’ll also work directly or indirectly with cloud-based services, including Twitter, Google TranslateTM, IBM Watson, Microsoft® Azure®, OpenMapQuest, PubNub and more. Features 500+ hands-on, real-world, live-code examples from snippets to case studies IPython + code in Jupyter® Notebooks Library-focused: Uses Python Standard Library and data science libraries to accomplish significant tasks with minimal code Rich Python coverage: Control statements, functions, strings, files, JSON serialization, CSV, exceptions Procedural, functional-style and object-oriented programming Collections: Lists, tuples, dictionaries, sets, NumPy arrays, pandas Series & DataFrames Static, dynamic and interactive visualizations Data experiences with real-world datasets and data sources Intro to Data Science sections: AI, basic stats, simulation, animation, random variables, data wrangling, regression AI, big data and cloud data science case studies: NLP, data mining Twitter®, IBM® WatsonTM, machine learning, deep learning, computer vision, Hadoop®, SparkTM, NoSQL, IoT Open-source libraries: NumPy, pandas, Matplotlib, Seaborn, Folium, SciPy, NLTK, TextBlob, spaCy, Textatistic, Tweepy, scikit-learn®, Keras and more Accompanying code examples are available here: http://ptgmedia.pearsoncmg.com/imprint_downloads/informit/bookreg/9780135224335/9780135224335_examples.zip. Register your product for convenient access to downloads, updates, and/or corrections as they become available. See inside book for more information.

Introduction To Data Science

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Author : Laura Igual
language : en
Publisher: Springer Nature
Release Date : 2024-04-12

Introduction To Data Science written by Laura Igual and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-04-12 with Computers categories.

This accessible and classroom-tested textbook/reference presents an introduction to the fundamentals of the interdisciplinary field of data science. The coverage spans key concepts from statistics, machine/deep learning and responsible data science, useful techniques for network analysis and natural language processing, and practical applications of data science such as recommender systems or sentiment analysis. Topics and features: Provides numerous practical case studies using real-world data throughout the book Supports understanding through hands-on experience of solving data science problems using Python Describes concepts, techniques and tools for statistical analysis, machine learning, graph analysis, natural language processing, deep learning and responsible data science Reviews a range of applications of data science, including recommender systems and sentiment analysis of text data Provides supplementary code resources and data at an associated website This practically-focused textbook provides an ideal introduction to the field for upper-tier undergraduate and beginning graduate students from computer science, mathematics, statistics, and other technical disciplines. The work is also eminently suitable for professionals on continuous education short courses, and to researchers following self-study courses.

Data Science With Python And R

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Author : Ian Stokes-Rees
language : en
Publisher:
Release Date : 2017

Data Science With Python And R written by Ian Stokes-Rees and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017 with categories.

"Data Science with Python and R LiveLessons is tailored to beginner data scientists seeking to use Python or R for data science. This course includes fundamentals of data preparation, data analysis, data visualization, machine learning, and interactive data science applications. Students will learn how to build predictive models and how to create interactive visual applications for their line of business using the Anaconda platform. This course will introduce data scientists to using Python and R for building on an ecosystem of hundreds of high performance open source tools."--Resource description page.

Marketing Data Science

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Author : Thomas W. Miller
language : en
Publisher: FT Press
Release Date : 2015-05-02

Marketing Data Science written by Thomas W. Miller and has been published by FT Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-05-02 with Business & Economics categories.

Now, a leader of Northwestern University's prestigious analytics program presents a fully-integrated treatment of both the business and academic elements of marketing applications in predictive analytics. Writing for both managers and students, Thomas W. Miller explains essential concepts, principles, and theory in the context of real-world applications. Building on Miller's pioneering program, Marketing Data Science thoroughly addresses segmentation, target marketing, brand and product positioning, new product development, choice modeling, recommender systems, pricing research, retail site selection, demand estimation, sales forecasting, customer retention, and lifetime value analysis. Starting where Miller's widely-praised Modeling Techniques in Predictive Analytics left off, he integrates crucial information and insights that were previously segregated in texts on web analytics, network science, information technology, and programming. Coverage includes: The role of analytics in delivering effective messages on the web Understanding the web by understanding its hidden structures Being recognized on the web – and watching your own competitors Visualizing networks and understanding communities within them Measuring sentiment and making recommendations Leveraging key data science methods: databases/data preparation, classical/Bayesian statistics, regression/classification, machine learning, and text analytics Six complete case studies address exceptionally relevant issues such as: separating legitimate email from spam; identifying legally-relevant information for lawsuit discovery; gleaning insights from anonymous web surfing data, and more. This text's extensive set of web and network problems draw on rich public-domain data sources; many are accompanied by solutions in Python and/or R. Marketing Data Science will be an invaluable resource for all students, faculty, and professional marketers who want to use business analytics to improve marketing performance.

Machine Learning And Deep Learning Using Python And Tensorflow

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Author : Venkata Reddy Konasani
language : en
Publisher: McGraw Hill Professional
Release Date : 2021-04-29

Machine Learning And Deep Learning Using Python And Tensorflow written by Venkata Reddy Konasani and has been published by McGraw Hill Professional this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-04-29 with Technology & Engineering categories.

Understand the principles and practices of machine learning and deep learning This hands-on guide lays out machine learning and deep learning techniques and technologies in a style that is approachable, using just the basic math required. Written by a pair of experts in the field, Machine Learning and Deep Learning Using Python and TensorFlow contains case studies in several industries, including banking, insurance, e-commerce, retail, and healthcare. The book shows how to utilize machine learning and deep learning functions in today’s smart devices and apps. You will get download links for datasets, code, and sample projects referred to in the text. Coverage includes: Machine learning and deep learning concepts Python programming and statistics fundamentals Regression and logistic regression Decision trees Model selection and cross-validation Cluster analysis Random forests and boosting Artificial neural networks TensorFlow and Keras Deep learning hyperparameters Convolutional neural networks Recurrent neural networks and long short-term memory