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.

Big data is the current hype, the thing you need to do to find the best job in the world. I’ve started using machine learning tools a decade ago, and when I saw this book, it felt like it was answering some concerns I had. Let’s see what’s inside.

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I work in an international company, and there are lots of people from different cultures around me, and with whom I need to interact. Out of the blue, it feels like it’s easy to work with all of them, I mean, how difficult could it be to work with them?

Actually, it’s easy, but sometimes interactions are intriguing and people do not react the way you expect them to react. And why is that? Lots of reasons, of course, but one of them is that they have a different culture and do not expect you to explicitly tell them what they did wrong (which is something I do. A lot).

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I have trouble with slides. I hate them. I’ve followed a training of presentation to make better ones, and with more or less no slides anymore. I liked that training very much, but it’s difficult to apply to scientific presentations. As such, I’ve decided to read this book who is about scientific presentations (published by IEEE-Wiley) and to see how other people apprehend slides.

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