R for Data Science

Learn how to use R to turn raw data into insight, knowledge, and understanding. This book introduces you to R, RStudio, and the tidyverse, a collection of R packages designed to work together to make data science fast, fluent, and fun. Suitable for readers with no previous programming experience, R for Data Science is designed to get you doing data science as quickly as possible. Authors Hadley Wickham and Garrett Grolemund guide you through the steps of importing, wrangling, exploring, and modeling your data and communicating the results. You’ll get a complete, big-picture understanding of the data science cycle, along with basic tools you need to manage the details. Each section of the book is paired with exercises to help you practice what you’ve learned along the way. You’ll learn how to: Wrangle—transform your datasets into a form convenient for analysis Program—learn powerful R tools for solving data problems with greater clarity and ease Explore—examine your data, generate hypotheses, and quickly test them Model—provide a low-dimensional summary that captures true "signals" in your dataset Communicate—learn R Markdown for integrating prose, code, and results

Produk Detail:

  • Author : Hadley Wickham
  • Publisher : "O'Reilly Media, Inc."
  • Pages : 492 pages
  • ISBN : 1491910364
  • Rating : 5/5 from 3 reviews
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R for Data Science

R for Data Science
  • Author : Hadley Wickham,Garrett Grolemund
  • Publisher : "O'Reilly Media, Inc."
  • Release : 12 December 2016
GET THIS BOOKR for Data Science

Learn how to use R to turn raw data into insight, knowledge, and understanding. This book introduces you to R, RStudio, and the tidyverse, a collection of R packages designed to work together to make data science fast, fluent, and fun. Suitable for readers with no previous programming experience, R for Data Science is designed to get you doing data science as quickly as possible. Authors Hadley Wickham and Garrett Grolemund guide you through the steps of importing, wrangling, exploring,

Python Data Science Handbook

Python Data Science Handbook
  • Author : Jake VanderPlas
  • Publisher : "O'Reilly Media, Inc."
  • Release : 21 November 2016
GET THIS BOOKPython Data Science Handbook

For many researchers, Python is a first-class tool mainly because of its libraries for storing, manipulating, and gaining insight from data. Several resources exist for individual pieces of this data science stack, but only with the Python Data Science Handbook do you get them all—IPython, NumPy, Pandas, Matplotlib, Scikit-Learn, and other related tools. Working scientists and data crunchers familiar with reading and writing Python code will find this comprehensive desk reference ideal for tackling day-to-day issues: manipulating, transforming, and

Introduction to Data Science

Introduction to Data Science
  • Author : Rafael A. Irizarry
  • Publisher : CRC Press
  • Release : 20 November 2019
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Introduction to Data Science: Data Analysis and Prediction Algorithms with R introduces concepts and skills that can help you tackle real-world data analysis challenges. It covers concepts from probability, statistical inference, linear regression, and machine learning. It also helps you develop skills such as R programming, data wrangling, data visualization, predictive algorithm building, file organization with UNIX/Linux shell, version control with Git and GitHub, and reproducible document preparation. This book is a textbook for a first course in data

Doing Data Science

Doing Data Science
  • Author : Cathy O'Neil,Rachel Schutt
  • Publisher : "O'Reilly Media, Inc."
  • Release : 09 October 2013
GET THIS BOOKDoing Data Science

Now that people are aware that data can make the difference in an election or a business model, data science as an occupation is gaining ground. But how can you get started working in a wide-ranging, interdisciplinary field that’s so clouded in hype? This insightful book, based on Columbia University’s Introduction to Data Science class, tells you what you need to know. In many of these chapter-long lectures, data scientists from companies such as Google, Microsoft, and eBay

Data Science

Data Science
  • Author : John D. Kelleher,Brendan Tierney
  • Publisher : MIT Press
  • Release : 13 April 2018
GET THIS BOOKData Science

A concise introduction to the emerging field of data science, explaining its evolution, relation to machine learning, current uses, data infrastructure issues, and ethical challenges. The goal of data science is to improve decision making through the analysis of data. Today data science determines the ads we see online, the books and movies that are recommended to us online, which emails are filtered into our spam folders, and even how much we pay for health insurance. This volume in the

Data Science Job: How to become a Data Scientist

Data Science Job: How to become a Data Scientist
  • Author : Przemek Chojecki
  • Publisher : Przemek Chojecki
  • Release : 31 January 2020
GET THIS BOOKData Science Job: How to become a Data Scientist

We’re living in a digital world. Most of our global economy is digital and the sheer volume of data is stupendous. It’s 2020 and we’re living in the future. Data Scientist is one of the hottest job on the market right now. Demand for data science is huge and will only grow, and it seems like it will grow much faster than the actual number of data scientists. So if you want to make a career change and

Data Science for Business

Data Science for Business
  • Author : Foster Provost,Tom Fawcett
  • Publisher : "O'Reilly Media, Inc."
  • Release : 27 July 2013
GET THIS BOOKData Science for Business

Written by renowned data science experts Foster Provost and Tom Fawcett, Data Science for Business introduces the fundamental principles of data science, and walks you through the "data-analytic thinking" necessary for extracting useful knowledge and business value from the data you collect. This guide also helps you understand the many data-mining techniques in use today. Based on an MBA course Provost has taught at New York University over the past ten years, Data Science for Business provides examples of real-world

Data Science

Data Science
  • Author : Vijay Kotu,Bala Deshpande
  • Publisher : Morgan Kaufmann
  • Release : 27 November 2018
GET THIS BOOKData Science

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 tenth project, this book will show you how to analyze data, uncover hidden patterns and relationships to aid important decisions and predictions. Data Science has become an essential tool to extract value from data for any organization that collects, stores and processes data as part of its operations. This

Data Science from Scratch

Data Science from Scratch
  • Author : Joel Grus
  • Publisher : "O'Reilly Media, Inc."
  • Release : 14 April 2015
GET THIS BOOKData Science from Scratch

Data science libraries, frameworks, modules, and toolkits are great for doing data science, but they’re also a good way to dive into the discipline without actually understanding data science. In this book, you’ll learn how many of the most fundamental data science tools and algorithms work by implementing them from scratch. If you have an aptitude for mathematics and some programming skills, author Joel Grus will help you get comfortable with the math and statistics at the core

Business Data Science: Combining Machine Learning and Economics to Optimize, Automate, and Accelerate Business Decisions

Business Data Science: Combining Machine Learning and Economics to Optimize, Automate, and Accelerate Business Decisions
  • Author : Matt Taddy
  • Publisher : McGraw Hill Professional
  • Release : 23 August 2019
GET THIS BOOKBusiness Data Science: Combining Machine Learning and Economics to Optimize, Automate, and Accelerate Business Decisions

Publisher's Note: Products purchased from Third Party sellers are not guaranteed by the publisher for quality, authenticity, or access to any online entitlements included with the product. Use machine learning to understand your customers, frame decisions, and drive value The business analytics world has changed, and Data Scientists are taking over. Business Data Science takes you through the steps of using machine learning to implement best-in-class business data science. Whether you are a business leader with a desire to go

Human-Centered Data Science

Human-Centered Data Science
  • Author : Cecilia Aragon,Shion Guha,Marina Kogan,Michael Muller,Gina Neff
  • Publisher : MIT Press
  • Release : 01 March 2022
GET THIS BOOKHuman-Centered Data Science

Best practices for addressing the bias and inequality that may result from the automated collection, analysis, and distribution of large datasets. Human-centered data science is a new interdisciplinary field that draws from human-computer interaction, social science, statistics, and computational techniques. This book, written by founders of the field, introduces best practices for addressing the bias and inequality that may result from the automated collection, analysis, and distribution of very large datasets. It offers a brief and accessible overview of many

DATA SCIENCE

DATA SCIENCE
  • Author : Dr.Venkataramana Sarella,Mr. Sandeep Srivastava,Dr.K.Jamberi,Dr.Syed Khasim
  • Publisher : GCS PUBLISHERS
  • Release : 01 May 2022
GET THIS BOOKDATA SCIENCE

DATA SCIENCE WRITTEN BY Dr.Venkataramana Sarella,Mr. Sandeep Srivastava, Dr.K.Jamberi, Dr.Syed Khasim

Introduction to Biomedical Data Science

Introduction to Biomedical Data Science
  • Author : Robert Hoyt,Robert Muenchen
  • Publisher : Lulu.com
  • Release : 25 November 2019
GET THIS BOOKIntroduction to Biomedical Data Science

Introduction to Biomedical Data Science aims to fill the data science knowledge gap experienced by many clinical, administrative and technical staff. The textbook begins with an overview of what biomedical data science is and then embarks on a tour of topics beginning with spreadsheet tips and tricks and ending with artificial intelligence. In between, important topics are covered such as biostatistics, data visualization, database systems, big data, programming languages, bioinformatics, and machine learning. The textbook is available as a paperback

Roundtable on Data Science Postsecondary Education

Roundtable on Data Science Postsecondary Education
  • Author : National Academies of Sciences, Engineering, and Medicine,Division of Behavioral and Social Sciences and Education,Division on Engineering and Physical Sciences,Board on Science Education,Computer Science and Telecommunications Board,Committee on Applied and Theoretical Statistics,Board on Mathematical Sciences and Analytics
  • Publisher : National Academies Press
  • Release : 02 October 2020
GET THIS BOOKRoundtable on Data Science Postsecondary Education

Established in December 2016, the National Academies of Sciences, Engineering, and Medicine's Roundtable on Data Science Postsecondary Education was charged with identifying the challenges of and highlighting best practices in postsecondary data science education. Convening quarterly for 3 years, representatives from academia, industry, and government gathered with other experts from across the nation to discuss various topics under this charge. The meetings centered on four central themes: foundations of data science; data science across the postsecondary curriculum; data science across society; and