Deep Dive Machine Learning Books
Intent 13 books
13 Machine Learning books for going deep into internals and theory. For those who want to truly understand — including Deep Learning and Designing Machine Learning Systems.
Rankings
1—
Deep Learning
Ian Goodfellow
121 in 90d
machine-learningai-ml
28.8
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2—
Designing Machine Learning Systems
Chip Huyen
1514 in 90d
machine-learningsystem-designai-ml
24.7
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3—
The Singularity Is Near
Ray Kurzweil
50 in 90d
machine-learningai-ml
12.5
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4—
Grokking Deep Learning
Andrew Trask
50 in 90d
machine-learningai-ml
12.5
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5—
Build a Large Language Model (from Scratch)
Sebastian Raschka
51 in 90d
llmmachine-learningai-ml
11.3
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6—
Superintelligence
Nick Bostrom
40 in 90d
machine-learningai-ml
10
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7—
Artificial Intelligence: A Modern Approach
Stuart Russell, Peter Norvig
31 in 90d
machine-learningai-ml
6.3
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8—
Pattern Recognition and Machine Learning
Christopher M. Bishop
21 in 90d
machine-learningdata-scienceai-ml
5.8
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9—
Reinforcement Learning: An Introduction
Richard S. Sutton, Andrew G. Barto
20 in 90d
machine-learningai-ml
5
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10—
The Elements of Statistical Learning
Trevor Hastie, Robert Tibshirani, Jerome Friedman
20 in 90d
machine-learningdata-scienceai-ml
5
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11—
Automating Inequality
Virginia Eubanks
20 in 90d
data-sciencemachine-learningdata
5
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12—
The Master Algorithm
Pedro Domingos
20 in 90d
machine-learningai-mldata
5
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13—
Hands-On Large Language Models
Jay Alammar, Maarten Grootendorst
21 in 90d
llmmachine-learningai-ml
3.8
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