################################################## ################################################## Books and websites in Machine Learning/Data Science ################################################## R: The official R introduction: https://cran.r-project.org/doc/manuals/r-release/R-intro.pdf (this can get quite technical but generally the first part of each section is readable and excellent). Nice interactive R intro: https://swirlstats.com/ Introduction to Data Science: Data Wrangling and Visualization with R (Chapman & Hall/CRC Data Science Series) 2nd Edition by Rafael A. Irizarry (Author) Introduction to Data Science: Data Analysis and Prediction Algorithms with R (Chapman & Hall/CRC Data Science Series) by Rafael A. Irizarry (Author) R for Data Science: Import, Tidy, Transform, Visualize, and Model Data 2nd Edition by Hadley Wickham (Author), Mine Cetinkaya-Rundel (Author), Garrett Grolemund (Author) https://r4ds.hadley.nz/ Getting help in R: https://www.r-project.org/help.html R Graphics Cookbook https://r-graphics.org/ Quantitative Social Science: An Introduction in tidyverse by Kosuke Imai and Nora Webb Williams | Aug 2, 2022 this one is more advanced (obviously): Advanced R, Second Edition (Chapman & Hall/CRC The R Series) 2nd Edition, by Hadley Wickham (Author) ################################################# Python: The help in Jupyter notebook is great! And places like python.org tend to be really good. Python Distilled (Developer's Library) Part of: Game Design (71 books) | by David Beazley | Sep 22, 2021 Introducing Python: Modern Computing in Simple Packages 2nd Edition, Kindle Edition by Bill Lubanovic (Author) Python Cookbook: Recipes for Mastering Python 3 Part of: Learning Python (7 books) | by David Beazley and Brian K. Jones, 3rd edition ################################################## Machine Learning/Data Science: An Introduction to Statistical Learning: with Applications in R (Springer Texts in Statistics) Part of: Springer Texts in Statistics (111 books) | by Gareth James , Daniela Witten , et al. | Jul 29, 2021, second edition An Introduction to Statistical Learning: with Applications in Python (Springer Texts in Statistics) Part of: Springer Texts in Statistics (111 books) | by Gareth James , Daniela Witten, et al. | Jul 1, 2023 The Elements of Statistical Learning: Data Mining, Inference, and Prediction, Second Edition (Springer Series in Statistics) Part of: Springer Series in Pharmaceutical Statistics (7 books) | by Trevor Hastie , Robert Tibshirani , et al. | Apr 21, 2017 Probabilistic Machine Learning: An Introduction (Adaptive Computation and Machine Learning series) Part of: Adaptive Computation and Machine Learning series (13 books) | by Kevin P. Murphy | Mar 1, 2022 Deep Learning (Adaptive Computation and Machine Learning series) Illustrated Edition by Ian Goodfellow (Author), Yoshua Bengio (Author), Aaron Courville (Author) this one is keras: Deep Learning with Python, Second Edition 2nd Edition by Francois Chollet (Author) (there is also an R version of the book). Deep Learning: Foundations and Concepts 2024th Edition by Christopher M. Bishop (Author), Hugh Bishop (Author) Machine Learning with PyTorch and Scikit-Learn: Develop machine learning and deep learning models with Python by Sebastian Raschka (Author), Yuxi (Hayden) Liu (Author), Vahid Mirjalili (Author) Machine Learning with R - Fourth Edition: Learn techniques for building and improving machine learning models, from data preparation to model tuning, evaluation, and working with big data 4th ed. Edition by Brett Lantz (Author) Python for Data Analysis: Data Wrangling with pandas, NumPy, and Jupyter 3rd Edition by Wes McKinney (Author) (first chunk is a very good is a very good, quick intro to python, numpy and pandas. Rest of book is detailed intro to data wrangling with python). Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow: Concepts, Tools, and Techniques to Build Intelligent Systems 3rd Edition by Aurelien Geron (Author) (very good tour of doing machine learning with Scikit-Learn, the fundamental python software for machine Learning) Python Data Science Handbook: Essential Tools for Working with Data 2nd Edition by Jake VanderPlas (Author) Linear Algebra and Optimization for Machine Learning: A Textbook 1st ed. 2020 Edition by Charu C. Aggarwal (Author) very nice webpage of ML/data science in R: https://cran.r-project.org/web/views/MachineLearning.html and of course: https://scikit-learn.org/stable/ ################################################## Computational Statistics: Computational Statistics by Geof H. Givens and Jennifer A. Hoeting | Nov 6, 2012 Probabilistic Machine Learning: An Introduction (Adaptive Computation and Machine Learning series) Part of: Adaptive Computation and Machine Learning series (13 books) | by Kevin P. Murphy | Mar 1, 2022 Computer Age Statistical Inference: Algorithms, Evidence, and Data Science (Institute of Mathematical Statistics Monographs, Series Number 5) Part of: Institute of Mathematical Statistics Monographs (4 books) | by Bradley Efron and Trevor Hastie | Jul 21, 2016 Surrogates: Gaussian Process Modeling, Design, and Optimization for the Applied Sciences (Chapman & Hall/CRC Texts in Statistical Science) 1st Edition by Robert B. Gramacy (Author) Computational Statistics in Data Science 1st Edition by Walter W. Piegorsch (Editor), Richard A. Levine (Editor), Hao Helen Zhang (Editor), Thomas C. M. Lee (Editor) Linear Algebra and Optimization for Machine Learning: A Textbook 1st ed. 2020 Edition by Charu C. Aggarwal (Author) Elements of Statistical Computing: NUMERICAL COMPUTATION 1st Edition by R. A. Thisted (Author) (old, but a classic) ################################################## C++ Accelerated C++: Practical Programming by Example 1st Edition by Andrew Koenig (Author), Barbara Moo (Author) (this is pretty old now, but it is still a great book) Tour of C++, A (C++ In-Depth Series) 3rd Edition by Bjarne Stroustrup (Author) 4.7 4.7 out of 5 stars (205) 4.3 on Goodreads 1,027 ratings (this is more up to data, Stroustrup is the author of C++) You might also want to get a book dedicated to the STL: Standard Template Library, which has many data structures and algorithms.