Title Page Copyright and Credits Hands-On Data Science with R About Packt Why subscribe? Packt.com Contributors About the authors About the reviewer Packt is searching for authors like you Preface Who this book is for What this book covers To get the most out of this book Download the example code files Download the color images Conventions used Get in touch Reviews Getting Started with Data Science and R Introduction to data science Key components of data science Computer science Predictive analytics (machine learning) Domain knowledge Active domains of data science Finance Healthcare Pharmaceuticals Government Manufacturing and retail Web industry Other industries Solving problems with data science Using R for data science Key features of R Our first R program UN development index Summary Quiz Descriptive and Inferential Statistics Measures of central tendency and dispersion Measures of central tendency Calculating mean, median, and mode with base R Measures of dispersion Useful functions to draw automated summaries Statistical hypothesis testing Running t-tests with R Decision rule – a brief overview of the p-value approach Be careful Running z-tests with R Elaborating a little longer A/B testing – a brief introduction and a practical example with R Summary Quiz Data Wrangling with R Introduction to data wrangling with R Data types, formats, and sources Data extraction, transformation, and load Basic tools of data wrangling Using base R for data manipulation and analysis Applying families of functions  Aggregation functions Merging DataFrames Using tibble and dplyr for data manipulation Basic dplyr usage Using select Filtering with filter Using arrange for sorting Summarise Sampling data The tidyr  package Converting wide tables into long tables Converting wide tables into long tables Joining tables dbplyr – databases and dplyr Using data.table for data manipulation Grouping operations Adding a column Ordering columns What is the advantage of searching using key by? Creating new columns in data.table Deleting a column Pivots on data.table The melt functionality Reading and writing files with data.table A special note on dates and/or time Miscellaneous topics Checking data quality Reading other file formats – Excel, SAS, and other data sources On-disk formats Working with web data Web APIs Tutorial – looking at airline flight times data Summary Quiz KDD, Data Mining, and Text Mining Good practices of KDD and data mining Stages of KDD Scraping a dwarf name Retrieving text from the web Legality of web scraping Web scraping made easy with rvest Retrieving tweets from R community  Creating your Twitter application  Fetching the number of tweets Cleaning and transforming data Looking for patterns – peeking, visualizing, and clustering data Peeking data Visualizing data Cluster analysis Summary Quiz Data Analysis with R Preparing data for analysis Data categories Data types in R Reading data Managing data issues Mixed data types Missing data Handling strings and dates Handling dates using POSIXct or POSIXlt Handling strings in R Reading data Combining strings Simple pattern matching and replacement with R Printing results Data visualisation Types of charts – basic primer Histograms Line plots Scatter plots Boxplots Bar charts Heatmaps Summarizing data Saving analysis for future work Packrat Checkpoint Rocker Summary Quiz Machine Learning with R What is machine learning? Machine learning everywhere Machine learning vocabulary Generic problems solved by machine learning Linear regression with R Tricks for lm Tree models Strengths and weakness The Chilean plebiscite data Starting with decision trees Growing trees with tree and rpart Random forests – a collection of trees Support vector machines What about regressions? Hierarchical and k-means clustering Neural networks Introduction to feedforward neural networks with R Summary Quiz Forecasting and ML App with R The UI and server Forecasting machine learning application Application details Summary Quiz Neural Networks and Deep Learning Daily neural nets Overview – NNs and deep learning Neuroscience inspiration ANN nodes Activation functions Layers Training algorithms NNs with Keras Getting things ready for Keras Getting practical with Keras Further tips Summary Quiz Markovian in R Markovian-type models Markovian models – real-world applications The Markov chain Programming an HMM with R Summary Quiz Visualizing Data Retrieving and cleaning data Crafting visualizations Summary Quiz Going to Production with R What is R Shiny? How to build a Shiny app Building an application inside R The reactive and isolate functions The observeEvent and eventReactive functions Approach for creating a data product from statistical modeling and web UI Some advice about Shiny Summary Quiz Large Scale Data Analytics with Hadoop Installing the package and Spark Manipulating Spark data using both dplyr and SQL Filtering and aggregating Spark datasets  Using Spark machine learning or H2O Sparking Water Providing interfaces to Spark packages Spark DataFrames within the RStudio IDE Summary Quiz R on Cloud Cloud computing Cloud types Things to look for Why Azure? Azure registration Azure Machine Learning Studio How modules work Building an experiment that uses R Summary  Quiz  The Road Ahead Growing your skills Gathering data Content to stay tuned to Meeting Stack Overflow Other Books You May Enjoy Leave a review - let other readers know what you think