Best Books
Top Data Sci + ML Books
Data Science and Machine Learning can be overwhelming! Gain stability navigating through this ever-changing landscape with the following recommended reads.
+Please add other book suggestions below in the comments.
#1 Automating Inequality: How High Tech Tools Profile, Police and Punish the Poor by Virginia Eubanks
#2 Natural Language Processing with Transformers by Lewis Tunstall, Leandro von Werra & Thomas Wolf
#3 Deep Learning with Python by François Chollet
#4 Naked Statistics by Charles Wheelan
#5 Weapons of Math Destruction by Cathy O’Neil
#6 Generative Deep learning by David Foster
#7 The Pattern On The Stone by W. Daniel Hillis
#8 The Book of Why by Dana Mackenzie and Judea Pearl
#9 Thinking, Fast and Slow by Daniel Kahneman
#10 Practical Statistics for Data Scientists by Peter Bruce, Andrew Bruce & Peter Gedeck
#11 Python for Data Analysis by Wes McKinney
#12 Algorithms of Oppression by Safiya Noble
#13 Hands-On Machine Learning with Scikit-Learn, Keras and Tensorflow
#14 Thinking in Systems by Donella H. Meadows
#15 The Manga Guide to Regression Analysis by Shin Takahashi
#16 Data Visualisation (2nd Edition) by Andy Krik
#17 The Age of Surveillance Capitalism by Shoshana Zuboff
#18 Interactive Data Visualization for the Web by Scott Murray
#19 The Better Angels of Our Nature by Steven Pinker
#21 Resisting AI by Dan McQuillan
#22 Enchantress of Numbers by Jennifer Chiavernini
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