Books I Reference
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.↩︎