Academic Resources - Data Science & Machine Learning

Version Control with Git and GitHub

• "Version Control with Git" by Software Carpentry Foundation
• Git cheat sheet
• GitHub flow guides
• GitHub flavored markdown guides
• Complete list of Github markdown emoji markup
• GitHub Classroom
• GitHub Education - hands-on experience for students, benefits for teachers and more.
• GitHub Pages
• GitHub Skills - "interactive courses for beginners and experts"

You can also download your favorite Octocat stickers.

Python Programming

• "Python Notes for Professionals" by GoalKicker.com
• "A Whirlwind Tour of Python" by Jake VanderPlas
• "Object-oriented Programming in Python for Mathematicians" by David A. Ham
• YouTube Series "Python Programming for Beginners Tutorials" by C.Schafer
• YouTube Series "Pandas Tutotials" by C.Schafer
• YouTube Series "Matplotlib Tutorials" by C.Schafer
• MicroPython

Mathematics for Machine Learning

• "Mathematics for Machine Learning" by Deisenroth, A. Aldo Faisal, and Cheng Soon Ong
• "Quantitative Economics with Python" by T.J.Sargent and J.Stachurski

Linear Algebra

• "Introduction to Applied Linear Algebra – Vectors, Matrices, and Least Squares" by S.Boyd and L.Vandenberghe
• YouTube Series "Essence of Linear Algebra" 3Blue1Brown by Grant Sanderson

Calculus

• YouTube "Essence of Calculus" 3Blue1Brown by Grant Sanderson
• "The Matrix Cookbook" by K.B.Petersen and M.S.Pedersen

Probability and Statistics

• "Introduction to Probability for Data Science" by Stanley H. Chan
• "Probabibility and Bayesian Modeling" by J.Albert and J.Hu
• "Probability, Statistics, and Random Processes For Electrical Engineering" by A. Leon-Garcia
• "First Course in Probability" by S.Ross
• "Think Stats" by Allen Downey
• "Think Bayes" by Allen Downey
• "Think DSP" by Allen Downey
• "Seeing Theory"
• MIT OpenCourseWare 6.041 "Probabilistic Systems Analysis and Applied Probability"

Data Science

• "Foundations of Data Science with Python" by J.M.Shea
• "Python Data Science Handbook" by J.VanderPlas
• "Data Analysis with Python" by FreeCodeCamp.org

Machine Learning

• "Pattern Recognition and Machine Learning" by C.Bishop
• "The Elements of Statistical Learning: Data Mining, Inference, and Prediction" by Trevor Hastie, Robert Tibshirani, and Jerome Friedman
• "Machine Learning - A First Course for Engineers and Scientists" by Andreas Lindholm, Niklas Wahlström, Fredrik Lindsten, and Thomas B. Schön
• "Pattern Recognition" by S.Theodoridis and K.Koutroumbas
• "Pattern Classification" by R.O.Duda, P.E.Hart, D.G.Stork
• "Python Machine Learning" by S.Raschka and V.Mirjalili
• "Machine Learning: A Probabilistic Perspective" by K.P.Murphy
• "Machine Learning: A Constrained-based Approach" by M.Gori
• "Human-in-the-Loop Machine Learning" by R.Monarch
• "Hands-On Machine Learning with Scikit-Learn and Tensorflow" by A.Géron
• "TinyML - Machine Learning with Tensorflow Lite on Arduino and Ultra-Low-Power Microcontrollers" by P.Warden and D.Situnayake
• YouTube "Neural Networks" 3Blue1Brown by Grant Sanderson
• "A Neural Network Playground" by TensorFlow
• "Pen and Paper Exercises in Machine Learning" by Michael U. Gutmann
• "Deep Learning Interviews: Hundreds of fully solved job interview questions from a wide range of key topics in AI" by Shlomo Kashani and Amir Ivry

Deep Learning

• "Introduction to Deep Learning" by E.Charniak
• "Deep Learning" by I.GoodFellow, Y.Bengio and A.Courville
• "Deep Learning with PyTorch" by E.Stevens, L.Antiga, T.Viehmann
• "Dive into Deep Learning" by A.Zhang, Z.C.Lipton, M.Li and A.J.Smola

Artificial Intelligence

• "Artificial Intelligence - A Modern Approach" by Stuart Russell and Peter Norvig
• "Reinforcement Learning - An Introduction" by R.Sutton and A.G.Barto
• "Feedback Systems: An Introduction for Scientists and Engineers" by K.J.Åström and R.M.Murray

Interpretable, Explainable & Fair AI

• "Interpretable Machine Learning - A Guide for Making Black Box Models Explainable" by Christoph Molnar
• "Fairness and Machine Learning - Limitations and Opportunities" by Solon Barocas, Moritz Hardt, Arvind Narayanan