Here's my curated list of the best data ml books for developers.
Quick Comparison
| Book | Author | Pages | Year |
|---|---|---|---|
| Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow | Aurélien Géron | 861 | 2022 |
| Designing Machine Learning Systems | Chip Huyen | 380 | 2022 |
| Python for Data Analysis | Wes McKinney | 579 | 2022 |
| Deep Learning with Python | François Chollet | 504 | 2021 |
| The Hundred-Page Machine Learning Book | Andriy Burkov | 160 | 2019 |
| Build a Large Language Model (From Scratch) | Sebastian Raschka | 368 | 2024 |
1. Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow
By Aurélien Géron · 861 pages · 2022
A solid data ml book that every developer should consider.
2. Designing Machine Learning Systems
By Chip Huyen · 380 pages · 2022
A solid data ml book that every developer should consider.
3. Python for Data Analysis
By Wes McKinney · 579 pages · 2022
A solid data ml book that every developer should consider.
4. Deep Learning with Python
By François Chollet · 504 pages · 2021
A solid data ml book that every developer should consider.
5. The Hundred-Page Machine Learning Book
By Andriy Burkov · 160 pages · 2019
A solid data ml book that every developer should consider.
6. Build a Large Language Model (From Scratch)
By Sebastian Raschka · 368 pages · 2024
A solid data ml book that every developer should consider.
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