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.↩︎