This entry is part 5 of 4 in the series Travelling in LLVM land

LLVM has always intrigued me. Actually, I always thought about one day writing a compiler. But it was more a challenge than a requirement for any of my works, private or professional, so never dived into it. The design of LLVM was also very well thought, and probably close to something I would have had liked to create.

So now the easiest is just to use LLVM for the different goals I want to achieve. I recently had to write clang-tidy rules, and I also want to perhaps create a JIT for Audio Toolkit and the modeling libraries. So lots of reasons to look at LLVM.

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This review will actually be quite quick: I haven’t finished the book and I won’t finish it.

The book was published in August 2015 and is based on OpenGL < 3. The authors may sometimes say that you can use shaders to do better, but the fact is that if you want to execute the code they propose, you need to use the backward compatibility layer, if it's available. OpenGL was published almost a decade ago, I can't understand why in 2015 two guys decided that a new book on scientific visualization should use an API that was deprecated a long time ago. What a waste of time. [amazon_enhanced asin="1782169725" /][amazon_enhanced asin="B01FGMWRO8" /]

Almost 18 months ago, I posted a small post on the first version of this book (http://blog.audio-tk.com/2013/09/04/book-building-machine-learning-systems-in-python/). At the time, I was really eager to see the second edition of it. And there it is!

I had once again the privilege of being a technical reviewer for this book, and I havce to say that the quality didn’t lower one bit, it went even higher. Of course, there is still room for a better book, when all Python module for Machine Learning are even better. I guess that will be for the third edition!

To get the book from the publisher: https://www.packtpub.com/big-data-and-business-intelligence/building-machine-learning-systems-python-second-edition

On other matters, the blog was quiet for a long time, I’m hoping to get some time to post a few new posts soon, but it is quite hard as I’m currently studying for another master’s degree!

I recently had the opportunity to be a technical reviewer for the new Building Machine Learning Systems in Python. As I took part in the book, I won’t write a review like what I did for other books.

First, I have to say that I was impressed by the quality of the content. Although I had some things that I thought were not excellent (I still need to check how my reviews changed the book), it’s the best book I’ve read from Packt so far. It has a good balance between code and comprehension, which is an equilibrium that is rarely achieved.

I don’t think it is possible to write a better book on Machine Learning in Python, unless the ecosystem evolves with new algorithms. Which it will, and it will mean a new edition of the book! Neat!