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" /]
After the announce of JUCE 5 release, I played a little bit with it, and then decided to read the only book on JUCE. It’s outdated and tackles JUCE 2.1.2. But who knows, it may be a gem?
Continue reading Book review: Getting Started With JUCE
C++ Multithreading Cookbook in 2014 (publication year), that seems quite interesting, with all the new stuff from the current C++ standard. Is it what the book delivers?
Continue reading Book review: C++ Multithreading Cookbook
There are now a few books on sickit-learn, for instance a general one on machine learning systems, and a cookbook. I was a technical reviewer for the first one, and now I’m reviewing the cookbook.
Continue reading Book review: scikit-learn Cookbook
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!
It seems that Packt Publishing is on a publishing spree on Machine Learning in Python. After Building Machine Learning Systems In Python for which I was technical reviewer, Packt published Learning Scikit-Learn In Python last November.
Continue reading Book review: Learning scikit-learn – Machine Learning in Python
I started using Boost.Asio years ago for my professional occupation. I remember difficult hours trying to understand its help and its tutorials. Would that have been different with the book?
Continue reading Book review: Boost.Asio C++ Network Programming
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!
I had the opportunity from Packt Publishing to review the second edition of Numpy Beginner’s Guide. Many thanks to the publisher for this and let’s go to the review.
Continue reading Book review: Numpy Beginner’s Guide
I had the opportunity from Packt Publishing to review Numpy Cookbook. Many thanks to the publisher for this and let’s go to the review.
Continue reading Book review: Numpy Cookbook