awesome/machine-learning
1
0
Fork 0
mirror of https://github.com/josephmisiti/awesome-machine-learning.git synced 2025-06-02 18:42:29 -04:00
Code Activity

Added one useful resource

Browse source 
Added the Machine Learning Books for Beginners URL to the section - Books, providing useful insights to aspiring ML engineers or working professionals.

Please let me know if further changes are required.

Thank you!
This commit is contained in:
Paras-96 2025-03-28 12:50:12 +05:30 • committed by GitHub
parent ae8a3d7b4f
commit 633d6ae7b8
No known key found for this signature in database
GPG key ID: B5690EEEBB952194
1 changed files with 1 additions and 0 deletions
Download patch file Download diff file Expand all files Collapse all files

1
README.md
View file

@ -1834,6 +1834,7 @@ be
* [Grokking Machine Learning](https://www.manning.com/books/grokking-machine-learning) - Grokking Machine Learning teaches you how to apply ML to your projects using only standard Python code and high school-level math.
* [Machine Learning Bookcamp](https://www.manning.com/books/machine-learning-bookcamp) - Learn the essentials of machine learning by completing a carefully designed set of real-world projects.
* [Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow](https://www.amazon.com/Hands-Machine-Learning-Scikit-Learn-TensorFlow/dp/1098125975) - Through a recent series of breakthroughs, deep learning has boosted the entire field of machine learning. Now, even programmers who know close to nothing about this technology can use simple, efficient tools to implement programs capable of learning from data. This bestselling book uses concrete examples, minimal theory, and production-ready Python frameworks (Scikit-Learn, Keras, and TensorFlow) to help you gain an intuitive understanding of the concepts and tools for building intelligent systems.
* [Machine Learning Books for Beginners](https://www.appliedaicourse.com/blog/machine-learning-books/) - This blog provides a curated list of introductory books to help aspiring ML professionals to grasp foundational machine learning concepts and techniques.
<a name="credits"></a>