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Machine Learning Book Collections

📚 Ultimate AI & Machine Learning Book Collection – Free Download

Welcome to the ultimate collection of books dedicated to Artificial Intelligence and Machine Learning! Whether you’re just starting out or looking to deepen your knowledge, this massive list of over 120+ handpicked books has something for everyone—from foundational topics to cutting-edge techniques in deep learning, data science, computer vision, NLP, and more.

We’ve curated this diverse set of learning materials to empower developers, data scientists, AI enthusiasts, and researchers with the best resources available—all in one place.

🔗 Download All Books From GitHub:

👉 GitHub Repository Link Here (Click here to download from GitHub)

📘 Complete Numbered Book List

Here’s the complete list of books included in the collection:

  1. Machine Learning by Tutorials: Beginning Machine Learning for Apple and iOS
  2. Artificial Neural Networks and Machine Learning – ICANN 2017
  3. Multisensor Data Fusion and Machine Learning for Environmental Remote Sensing
  4. Hands-On Machine Learning with Scikit-Learn and TensorFlow
  5. Pro Machine Learning Algorithms: A Hands-On Approach in Python and R
  6. Python Machine Learning
  7. Introduction to Machine Learning with Python
  8. A Beginner’s Tutorial for Machine Learning Beginners
  9. Machine Learning: A Probabilistic Perspective
  10. Machine Learning for Hackers
  11. Pro Machine Learning Algorithms
  12. Machine Learning in Bioinformatics
  13. Practical Machine Learning with Python
  14. Practical Machine Learning with Python: A Problem-Solver’s Guide
  15. Handbook of Statistics: Machine Learning – Theory and Applications
  16. Predictive Analytics with Microsoft Azure Machine Learning, 2nd Edition
  17. Advances in Financial Machine Learning
  18. Financial Signal Processing and Machine Learning
  19. Keras to Kubernetes: The Journey of a Machine Learning Model to Production
  20. Hands-On Machine Learning with Scikit-Learn and TensorFlow (Alt. Version)
  21. Machine Learning with PySpark
  22. Introducing Data Science: Big Data, ML, and More Using Python
  23. Genetic Algorithms and Machine Learning for Programmers
  24. An Introduction to Machine Learning – Summer School
  25. Applied Text Analysis with Python
  26. Introducing Data Science (Duplicate Entry)
  27. Machine Learning con Python
  28. Machine Learning in Python
  29. Practical Machine Learning with Python (Alt. Version)
  30. From Curve Fitting to Machine Learning
  31. Demystifying Big Data and Machine Learning for Healthcare
  32. State-Space Approaches for Modelling in Financial Engineering
  33. Applied Deep Learning
  34. AI for Business: What You Need to Know
  35. Deep Learning: Practical Neural Networks with Java
  36. Deep Learning: Practical Neural Networks with Java (Alt. Version)
  37. Machine Learning Refined
  38. Machine Learning Refined (Alt. Version)
  39. Machine Learning with TensorFlow (Alt. Version)
  40. Predictive Analytics
  41. Signal Processing and Machine Learning for Brain–Machine Interfaces
  42. Mastering Machine Learning with Python in Six Steps
  43. Machine Learning in Action
  44. Explainable and Interpretable Models in ML
  45. Principles And Theory For Data Mining and ML
  46. Principles And Theory For Data Mining and ML (Alt. Version)
  47. Blockchain Enabled Applications
  48. Python Machine Learning (Duplicate Entry)
  49. Numerical Algorithms for ML and Graphics
  50. Thoughtful Machine Learning in Python

(…and many more—up to 130+ books!)


📌 Topics Covered:

  • Supervised & Unsupervised Learning
  • Deep Learning (CNNs, RNNs, LSTMs)
  • Reinforcement Learning
  • Natural Language Processing
  • Data Science & Statistics
  • Real-world AI Applications in Business & Healthcare
  • ML using Python, R, TensorFlow, Scikit-learn, H2O, and Spark
  • Ethics, Explainability, and ML Interpretability
  • Machine Learning for Big Data, Finance, and IoT

🚀 Why This Collection?

  • ✅ Curated for both beginners and professionals
  • ✅ Combines academic resources and practical guides
  • ✅ Suitable for developers, researchers, data scientists, and AI learners
  • ✅ Covers a wide range of frameworks, languages, and domains

📥 Ready to Dive In?

Grab your copy now from our GitHub repo and take your AI/ML learning journey to the next level!

👉 Download All from GitHub (More Books on GitHub repo link here)

Thanks for other contributors for providing the softcopy and this helps the new developers to upskill.

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