Introduction to Data Science



Download free course Introduction to Data Science, pdf file on 722 pages by Rafael A Irizarry.
The demand for skilled data science practitioners in industry, academia, and government is rapidly growing. This book 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 with dplyr, data visualization with ggplot2, algorithm building with caret, file organization with UNIX/Linux shell, version control with Git and GitHub, and reproducible document preparation with knitr and R markdown. The book is divided into six parts: R, Data Visualization, Data Wrangling, Probability, Inference and Regression with R, Machine Learning, and Productivity Tools. Each part has several chapters meant to be presented as one lecture. The book includes dozens of exercises distributed across most chapters.

Table of contents

  • R
  • Getting Started with R and RStudio
  • R Basics
  • Programming basics
  • The tidyverse
  • Importing data
  • Data Visualization
  • Introduction to data visualization
  • ggplot2
  • Visualizing data distributions
  • Data visualization in practice
  • Data visualization principles
  • Robust summaries
  • Statistics with R
  • Introduction to Statistics with R
  • Probability
  • Random variables
  • Statistical Inference
  • Statistical models
  • Regression
  • Linear Models
  • Association is not causation
  • Data Wrangling
  • Introduction to Data Wrangling
  • Reshaping data
  • Joining tables
  • Web Scraping
  • String Processing
  • Parsing Dates and Times
  • Text mining
  • Machine Learning
  • Introduction to Machine Learning
  • Smoothing
  • Cross validation
  • The caret package
  • Examples of algorithms
  • Machine learning in practice
  • Large datasets
  • Clustering
  • Productivity tools
  • Introduction to productivity tools
  • Organizing with Unix
  • Git and GitHub
  • Reproducible projects with RStudio and R markdown
Pages : 722
Size : 55.8 MB
File type : PDF
Downloads: 222
Created: 2022-02-03
License: CC BY-NC-SA
Author(s): Rafael A Irizarry
Introduction to Data Science

Warning: Trying to access array offset on false in /home/tutovnfz/public_html/article.php on line 233

Others Computer science Tutorials

Learn BlackBerry 10 App Development

Ernst Denert Award for Software Engineering 2019

SAT/SMT by Example

Games and Rules

Blockchain and Crypt Currency

Others related eBooks about Introduction to Data Science

Kubernetes for Full-Stack Developers

Download free course Kubernetes for Full-Stack Developers, pdf file on 637 pages by Jamon Camisso, Hanif Jetha, Katherine Juell....

Rethinking Productivity in Software Engineering

This open access book collects the wisdom of a seminar on productivity in software engineering, a meeting of community leaders, who came together with the goal of rethinking traditional definitions and measures of productivity....

Machine Learning: The Complete Guide

Machine learning is one of the fastest growing areas of computer science, with far-reaching applications. The aim of this textbook is to introduce machine learning, and the algorithmic paradigms it offers, in a principled way. The book provides an extensive theoretical account of the fundamental ide...

Keras Succinctly

Download free course Keras Succinctly, pdf file on 105 pages by James McCaffrey....

Introductionto the Assembly Language

This tutorial represente a brief introduction to assembly programming ,training courses in PDF under 77 pages designated to beginners....

Arduino : RFID Start Guide

This pdf tutorial is an overview about Arduino and RFID ,you will learn how to add an Radio Frequency Identification to your Arduino project....

unity3d PDF Tutorial

Download free unity3d tutorial course in PDF, training file in 40 chapters and 219 pages. Free unaffiliated ebook created from Stack OverFlow contributor....

Microservices vs Service-Oriented Architecture (SOA)

For anyone who has been developing web applications for 10 years or more, the recent rise of microservices sounds a lot like a development approach we already knew - service-oriented architecture (SOA). Both architectures are focused on breaking up large monolithic applications into collections of...

Making Servers Work

Download free course Making Servers Work, pdf file on 281 pages by Jamon Camisso....

Measure, Integration and Real Analysis

This textbook welcomes students into the fundamental theory of measure, integration, and real analysis. Focusing on an accessible approach, it lays the foundations for further study by promoting a deep understanding of key results. ...