Comparison review between first and second edition of Hands on Machine Learning with Scikit-Learn, Keras and TensorFlow

The best introduction, the best practical introduction to machine learning that I’ve ever seen and I really do. I think it’s an excellent book and a lot of people agree with me. Well at the end of year 2019  the second edition of Hands on Machine Learning with Scikit-Learn, Keras and TensorFlow came out and the question is is this book as Good As the first edition? Let’s take a look. From my observation this second edition is far better than the 1st edition. 

What is new in 2nd edition?

It has 250 extra pages. Let’s take a look at the index. So you get an overall description of machine learning then get an end-to-end machine learning project. So what I like about this book is that it starts to sort of a high level and then you go into more details differences from the other book, but we have this section on unsupervised learning techniques specifically k-means and Gaussian mixture as they weren’t in the previous one and then the section on neural networks has been expanded and there’s a nice section on deep computer vision using convolutional neural networks. Look at also been updated to cover TensorFlow to and carers. I think this is even better than the first addition. It has an expanded version of the first edition and it has all the strengths of the first edition plastic covers extra topics. All python codes are updated according to TensorFlow. 2.0 . There is a well introduction of high-level Keras API. This new edition covered enough about TensorFlow data API, Eager Execution, Estimator API , deployment on Google cloud ML, embedding, how to handle time series and many more topics are included in this new edition.

Why do I like this book?

Why do I like it? I like the way it starts with a high level  explanation of the field and then you get in Chapter 2 an end-to-end machine learning project to follow through which gives the rest of the book context. The topics are very well explained. There’s a lot of code and no code examples and it’s very well presented by the time you’ve gone through this you will understand the topic very well and in Practical terms, you’ll understand how to implement and build your own projects. 

Some criticisms about this book:

Some criticisms of the book are that it’s not for beginners, you know, it’s a little bit too advanced for beginners. And whilst You could argue that that is true if you’ve never done any python before you don’t know linear algebra or a little bit of calculus, you might get a bit lost, but I think for the really motivated beginner it would be very good. So even if that is you even if you don’t know any python, you’ll go away and learn enough python and to be able to go with the book and if you don’t know enough math, you’ll be able to go and learn enough maths.The fact is you can teach yourself those things and then pursue them with the book.


But it is true that it’s not for absolute beginners. So if you feel that you are an absolute beginner, Perhaps just read up, learn a little bit of python and just enough math to be able then to start using this book. The other thing about this book is that it’s for determined readers only if you’re just a little bit interested in machine learning and wandering here how it might be implemented using python this book won’t be for you because you know to be able to learn from this book you’ve got to be very motivated to want to get all the way through it. The things in this book are the topics that are covered are you know, they’re complex they’re challenging and they will require thought this isn’t bedtime reading. It’s going to take you if you’re a beginner a good few months to get through it, but that’s no bad thing because it’s so comprehensive. You’ll know the subject very well.


The price of this book for such a comprehensive book on the subject I think is extremely good value and if you look at the cost of machine learning courses out there it Compares very favorably to that. So if you are determined, you know if you’re determined to learn machine learning if you’re very motivated to learn machine learning and learning using python, I would very much recommend this book to you.

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