Free Machine Learning with Python cookbooks (PDF)

There are several great Machine Learning with Python cookbooks available, each with its own strengths and focuses. Here are a few popular ones:

• "Python Machine Learning Cookbook" by Chris Albon: 

This cookbook covers a wide range of topics in machine learning, from data cleaning and preparation to model selection and evaluation. It includes practical examples and code snippets to help readers apply the concepts covered in the book.

• "Applied Machine Learning" by Kelleher and Tierney: 

This book takes a practical approach to machine learning, covering topics such as data preparation, feature engineering, and model selection. It includes code examples in Python and R and provides guidance on how to apply machine learning techniques to real-world problems.

• "Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow" by Aurélien Géron:

This popular book covers a broad range of topics in machine learning, including classification, regression, clustering, and deep learning. It includes practical examples and code snippets using popular Python libraries such as scikit-learn, Keras, and TensorFlow.

• "Python Machine Learning" by Raschka and Mirjalili: 

This book covers a wide range of topics in machine learning, including data preprocessing, classification, regression, clustering, and deep learning. It includes code examples in Python and provides guidance on how to implement machine learning algorithms from scratch.

Ultimately, the best Machine Learning with Python cookbook for you will depend on your background, interests, and learning goals. I recommend reviewing the table of contents and sample chapters of each book to determine which one best aligns with your needs.