Uploaded February 2020 | Updated September 2026, 2 weeks ago
I saw many questions on forums, facebook groups, everywhere about how to select the best book to learn Python. Or the best book to learn Machine Learning or Deep Learning.
For this I recommend "Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow: Concepts, Tools, and Techniques to Build Intelligent Systems. 2nd Edition" by by Aurélien Géron.
Firstly, because of well-prepaid structure. The book contain straight-forward journey from the very basics of what is Machine Learning to deeply and complicated cases using different techniques in Scikit-learn, Tensorflow and Keras with piece of code and short and clear explanations. What is really impressed me – the color printed graphs and schemes.
In the end of each chapter you will find lists of questions that covering all must known points for specific topic in chapter. All the answers are provided in the end of the book with rich explanations and examples. You can use those materials in you daily works, preparing for interviews or remember what is the most important for topic you are doing.
If you are interesting in only one specific topic, just find the keyword or term in table of content or in Index. For this you do not need to read chapter from beginning. Just read the part of chapter you are interesting in.
The main difference from the first edition in my opinion that this book now covers newer versions of Machine Learning and Deep Learning packages, include Keras into the readings. Eve, how to deploy your model to Google Cloud.
If you check the table of the content of the book, you will be surprised to having many Machine learning and Deep Learning courses in one place, in your hands.
This book provide only the piece of code, not full Python code from totally zero to end-to-end in major part of examples. That is not possible in printed book. By solving this issue, author provides books‘ notebook in github where you can study your examples with full Python codes having the book on another hand.
Github link: github.com/ageron/handson-ml2
Happy coding. Vytautas.
#mlbook
#aibook
#datasciencebookreview
I saw many questions on forums, facebook groups, everywhere about how to select the best book to learn Python. Or the best book to learn Machine Learning or Deep Learning.
For this I recommend "Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow: Concepts, Tools, and Techniques to Build Intelligent Systems. 2nd Edition" by by Aurélien Géron.
Firstly, because of well-prepaid structure. The book contain straight-forward journey from the very basics of what is Machine Learning to deeply and complicated cases using different techniques in Scikit-learn, Tensorflow and Keras with piece of code and short and clear explanations. What is really impressed me – the color printed graphs and schemes.
In the end of each chapter you will find lists of questions that covering all must known points for specific topic in chapter. All the answers are provided in the end of the book with rich explanations and examples. You can use those materials in you daily works, preparing for interviews or remember what is the most important for topic you are doing.
If you are interesting in only one specific topic, just find the keyword or term in table of content or in Index. For this you do not need to read chapter from beginning. Just read the part of chapter you are interesting in.
The main difference from the first edition in my opinion that this book now covers newer versions of Machine Learning and Deep Learning packages, include Keras into the readings. Eve, how to deploy your model to Google Cloud.
If you check the table of the content of the book, you will be surprised to having many Machine learning and Deep Learning courses in one place, in your hands.
This book provide only the piece of code, not full Python code from totally zero to end-to-end in major part of examples. That is not possible in printed book. By solving this issue, author provides books‘ notebook in github where you can study your examples with full Python codes having the book on another hand.
Github link: github.com/ageron/handson-ml2
Happy coding. Vytautas.
#mlbook
#aibook
#datasciencebookreview
