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Putting the books listed below into three categories based on complexity
I: Mathematical Theory
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1. Deep Learning
Book by Aaron Courville, Ian Goodfellow, and Yoshua Bengio
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5. Pattern Recognition and Machine Learning
Book by Christopher Bishop
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8. Understanding Machine Learning: From Theory to Algorithms
Textbook by Shai Ben-David and Shai Shalev-Shwartz
II: Mix of Theory and Applied Study
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2. Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow
Concepts, Tools, and Techniques to Build Intelligent Systems
Book by Aurelien Geron
III: Applied Study
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6. The Hundred-Page Machine Learning Book
Book by Andriy Burkov
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9. Machine Learning for Absolute Beginners: A Plain English Introduction
Book by O. Theobald
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52. Machine Learning in Python (Essential Techniques For Predictive Analysis)
By: Michael Bowles
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53. Fifty Algorithms Every Programmer Should Know (2e)
By: Imran Ahmad (PhD)
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54. Applied Machine Learning and AI for Engineers
Solve Business Problems That Can't Be Solved Algorithmically (Release 1)
Jeff Prosise
O’Reilly Media, Inc. (2022)
All
1. Deep Learning
Book by Aaron Courville, Ian Goodfellow, and Yoshua Bengio
2. Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow
Concepts, Tools, and Techniques to Build Intelligent Systems
Book by Aurelien Geron
3. The Elements of Statistical Learning
Book by Jerome H. Friedman, Robert Tibshirani, and Trevor Hastie
4. An Introduction to Statistical Learning: With Applications in R
Book
5. Pattern Recognition and Machine Learning
Book by Christopher Bishop
6. The Hundred-Page Machine Learning Book
Book by Andriy Burkov
7. Deep Learning with Python
Book by François Chollet
8. Understanding Machine Learning: From Theory to Algorithms
Textbook by Shai Ben-David and Shai Shalev-Shwartz
9. Machine Learning for Absolute Beginners: A Plain English Introduction
Book by O. Theobald
10. Python Machine Learning
Book by Sebastian Raschka
11. Artificial Intelligence: A Modern Approach
Textbook by Peter Norvig and Stuart J. Russell
12. Introduction to Machine Learning
Textbook by Ethem Alpaydın
13. Machine Learning: A Probabilistic Perspective
Textbook by Kevin P. Murphy
14. Machine Learning for Hackers
Book by Drew Conway and John Myles White
15. Programming Collective Intelligence
Book: O'Reilly
16. Machine Learning For Dummies
Book by John Mueller and Luca Massaron
17. Bayesian Reasoning and Machine Learning
Book by David Barber
18. Reinforcement Learning: An Introduction
Book by Andrew Barto and Richard S. Sutton
19. Learning from Data: A Short Course
Book by Hsuan-Tien Lin, Malik Magdon-Ismail, and Yaser Abu-Mostafa
20. Machine Learning in Action
Book by Peter Harrington
21. Machine Learning: The Art and Science of Algorithms that Make Sense of Data
Book by Peter Flach
22. Introduction to Machine Learning with Python
A Guide for Data Scientists
Author(s): Andreas C. Müller, Sarah Guido
Publisher: O’Reilly Media, Year: 2016
23. Fundamentals of Machine Learning for Predictive Data Analytics: Algorithms, Worked Examples, and Case Studies
Textbook by Aoife D'Arcy, Brian Mac Namee, and John D. Kelleher
24. Mining of Massive Datasets
Book by Anand Rajaraman and Jeffrey Ullman
25. Foundations of Machine Learning
Textbook by Afshin Rostamizadeh, Ameet Talwalkar, and Mehryar Mohri
26. Superintelligence: Paths, Dangers, Strategies
Book by Nick Bostrom
27. Make Your Own Neural Network: A Gentle Journey Through the Mathematics ...
Book by Tariq Rashid
28. Python Machine Learning: Machine Learning and Deep Learning with Python, Scikit-learn, and TensorFlow 2, 3rd Edition
Book by Sebastian Raschka and Vahid Mirjalili
29. Machine Learning: An Algorithmic Perspective
Book by Stephen Marsland
30. The Master Algorithm: How the Quest for the Ultimate Learning Machine Will Remake Our World
Book by Pedro Domingos
31. Grokking Deep Learning
Book by Andrew W. Trask
32. Advances in Financial Machine Learning
Book by Marcos Lopez de Prado
33. Machine Learning: A Guide to Current Research
Book by Tom M. Mitchell
34. Pattern Classification
Book by David G. Stork, Peter E. Hart, and Richard O. Duda
35. Building Machine Learning Systems with Python - Second Edition
Book by Luis Pedro Coelho and Willi Richert
36. Bayesian Methods for Hackers: Probabilistic Programming and Bayesian Inference
Book by Cameron Davidson-Pilon
37. Information Theory, Inference and Learning Algorithms
Textbook by David J. C. MacKay
38. Probabilistic Graphical Models: Principles and Techniques
Book by Daphne Koller and Nir Friedman
39. Interpretable Machine Learning
Book by Christoph Molnar
40. The Book of Why: The New Science of Cause and Effect
Book by Dana Mackenzie and Judea Pearl
41. Fundamentals of Deep Learning: Designing Next-Generation Machine Intelligence Algorithms
Book by Nicholas Locascio and Nikhil Buduma
42. Deep Reinforcement Learning Hands-On: Apply Modern RL Methods, with Deep Q-networks, Value Iteration, Policy Gradients, TRPO, AlphaGo Zero and More
43. Think Stats
Book by Allen B. Downey
44. Gaussian Processes for Machine Learning
Book by Carl Edward Rasmussen and Christopher K. I. Williams
45. Data Mining: Practical Machine Learning Tools and Techniques
Book
46. Machine Learning with R
Book by Brett Lantz
47. Python Data Science Handbook: Essential Tools for Working with Data
Book by Jake VanderPlas
48. Real world machine learning: video edition
Book by Henrik Brink, Joseph Richards, and Mark Fetherolf
49. Machine Learning Algorithms: Popular Algorithms for Data Science and Machine Learning
Book by Giuseppe Bonaccorso
50. Machine Learning: A Bayesian and Optimization Perspective
Book by Sergios Theodoridis
51. Mathematics for Machine Learning
Textbook by A. Aldo Faisal, Cheng Soon Ong, and Marc Peter Deisenroth
52. Machine Learning in Python (Essential Techniques For Predictive Analysis)
By: Michael Bowles
53. Fifty Algorithms Every Programmer Should Know (2e)
By: Imran Ahmad (PhD)
54. Applied Machine Learning and AI for Engineers
Solve Business Problems That Can't Be Solved Algorithmically (Release 1)
Jeff Prosise
O’Reilly Media, Inc. (2022)
Tags: List of Books,Machine Learning,
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