# Books I Reference

Books

A list of Data Science books I reference

The full list of the books in my shelf is on my Goodreads account ^{1}. The ones I refer to the most are listed here:

Deep Learning | |

Deep Learning with R | Francois Chollet |

Handbook Of Neural Computing Applications | Alianna J Maren |

Deep Learning | Ian Goodfellow |

LSTM with Python | Jason Brownlee |

GLM | |

Generalized Additive Models: An Introduction with R, Second Edition | Simon Wood |

Applied Regression Modeling | Iain Pardoe |

Generalized Linear Models | John P. Hoffmann |

Introduction to Linear Regression Analysis | Douglas Montgomery |

ML | |

Hands-On Machine Learning with Scikit-Learn and Tensorflow: Concepts, Tools, and Techniques to Build Intelligent Systems | Aurelien Geron |

Flexible Imputation of Missing Data | Stef van Buuren |

Applied Predictive Modeling | Max Kuhn |

An Introduction to Statistical Learning: With Applications in R | Trevor Hastie |

Python | |

Python for Data Analysis | Wes McKinney |

Introducing Python: Modern Computing in Simple Packages | Bill Lubanovic |

Python Cookbook | David Beazley |

Quality | |

Multivariate Statistical Quality Control Using R | Edgar Santos |

Statistics for Experimenters: Design, Innovation, and Discovery | George Box |

Quality Control with R: An ISO Standards Approach | Emilio L Cano |

Design and Analysis of Experiments with R | John Lawson |

R | |

R for Data Science: Import, Tidy, Transform, Visualize, and Model Data | Hadley Wickham |

Testing R Code | Richard Cotton |

R Packages | Hadley Wickham |

Advanced R | Hadley Wickham |

Stats | |

The Essentials of Probability | Richard Durrett |

Probability and Statistical Inference | Robert Hogg |

Applied Multivariate Statistical Analysis | Richard Johnson |

Multivariate Statistical Methods | Donald Morrison |

Mathematical Statistics and Data Analysis | John Rice |

Best Practices in Data Cleaning: A Complete Guide to Everything You Need to Do Before and After Collecting Your Data | Jason Osborne |

Multivariable Modeling and Multivariate Analysis for the Behavioral Sciences | Brian Everitt |

Text | |

Natural Language Processing with Python | Steven Bird |

Text Mining with R | Julia Silge |

Visualization | |

Information Dashboard Design: Displaying Data for At-a-Glance Monitoring | Stephen Few |

Lattice: Multivariate Data Visualization with R | Deepayan Sarkar |

ggplot2: Elegant Graphics for Data Analysis | Hadley Wickham |

Data Visualisation: A Handbook for Data Driven Design | Andy Kirk |

## Footnotes

Most of them are a result of my MSPA coursework. Others are from colleagues. I’m always searching for good literature to study from. If you have suggestions, please drop me a note.↩︎