Mikhail Oksenenko

Mastering Artificial Intelligence

Part I. Intro

1. The Master Algorithm (Pedro Domingos)
2. Quand la machine apprend (Yann Le Cun) +ru
3. Make Your Own Neural Network (Tariq Rashid)

Part II. Foundation

4. Deep Learning from Scratch (Seth Weidman)
5. Deep Learning with Python (François Chollet)
6. Deep Learning and the Game of Go (Max Pumperla)

Part III. Advanced

7. Generative Deep Learning (David Foster)
8. Hands-On Large Language Models (Jay Alammar)
9. Build a Large Language Model (From Scratch) (Sebastian Raschka)

Part IV. Grok

10. Introduction to Machine Learning with Python (Andreas C. Müller)
11. Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow (Aurélien Géron)
12. Machine Learning with PyTorch and Scikit-Learn (Sebastian Raschka)

Part V. Tools

13. Python for Data Analysis (Wes McKinney)
14. Python Data Science Handbook (Jake VanderPlas)
15. Modern Time Series Forecasting with Python (Manu Joseph)

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Articles

• Attention Is All You Need
• DeepSeek-OCR: Contexts Optical Compression

Articles (Titans)

• Titans: Learning to Memorize at Test Time
• It's All Connected: A Journey Through Test-Time Memorization, Attentional Bias, Retention, and Online Optimization
• Nested Learning: The Illusion of Deep Learning Architectures
• Titans Revisited: A Lightweight Reimplementation and Critical Analysis of a Test-Time Memory Model

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