Here are some key details about the book:
Audience: The book is intended for developers and data scientists who have some prior experience in Python programming and want to get started with machine learning or enhance their existing knowledge.
Coverage:
- The initial sections of the book focus on machine learning using Scikit-Learn, introducing concepts like regression, classification, and clustering.
- It then dives into neural networks and deep learning using Keras and TensorFlow.
- Throughout the book, readers work on real-world datasets and projects to understand and apply the concepts.
- Hands-On Approach: True to its name, the book emphasizes practical exercises and provides Jupyter notebooks that guide the readers through the various ML and deep learning techniques.
Concepts: Apart from coding and implementation, Géron also dives into the theory behind various algorithms, ensuring that readers not only know how to use a tool but also understand the principles behind it.
