Introduction to Machine Learning Using Python

As a beginner, it came to me as a surprise that there is a lot of Python code to go through, and the extensive Python code intimidated me and many other people as well. The point of using Python code I am told is to show how accessible machine learning is with the online resources available today. So with that in mind, is the Geron book "Hands-On Machine Learning with Scikit-Learn and TensorFlow: Concepts, Tools, and Techniques to Build Intelligent Systems" a good beginner's book if you don't have much experience working with Python code?

Machine Learning: An Algorithmic Perspective by Stephen Marsland is a book that is on the more mathematically oriented end of the Python machine learning spectrum. Despite the mathematical approach, there is still plenty of Python code and thus the book can be read "at the computer".

Absolute beginners will be looking for the #1 book to start with. Some Chegg experts recommended Machine Learning For Dummies just because of its precise clarity and slow teaching style. Do you agree or disagree?

The Head First book series has gained a reputation for beginner-friendly programming books that are nonetheless definitive. Learning Python from this book takes the readers from the basics to an intermediate level of knowledge. The multitude of coding exercises covers areas like working with dictionaries and sets. In addition, more advanced techniques like threading and building web apps are also covered. But is this a good book for beginners and people who are intimidated by Python code?