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!
Yet another book that my colleague suggested me to read. I also discussed it with another colleague who told me the same: this is a book that anyone in the oil and gas field should read. And what about people not in this industry?
Continue reading Book review: The Prize – The Epic Quest for Oil, Money & Power
I worked for a long time for the seismic department of my company, and switched to the reservoir department only last year. The problems that are tackled are quite different, and the way they are solved as well. So nothing to do with the book I reviewed a long time ago. So after 2 trainings in reservoir simulation, I also read this book that a colleague of mine labeled as the reference book.
Continue reading Book review: Fundamentals of Reservoir Engineering
How to know whether or not to produce an oil field, and how to know how? The oil industry is used to make a lot of simulations to satisfy the SEC rules, and to know how much oil they can drill today and in the future. This book goes further than just the usual how much from a field under specific condition, by adding the development plan as well as the oil price in the equation.
Continue reading Book review: Intelligent Systems in Oil Field Development under Uncertainty
Nice title, surfing on the many core hype, and with a practical approach! What more could one expect from a book on such an interesting subject?
Continue reading Book review: Machine Learning for Adaptive Many-Core Machines – A Practical Approach
There are a lot of books on software project management best practices. But usually, they are not guides to work with people. And it is people who make projects, not money or computers.
Continue reading Book review: It Sounded Good When We Started – A Project Manager’s Guide to Working with People on Projects
When I developed my first tool based on genetic algorithms, it was to replace local optimization algorithm (“Simulated Annealing”, as advertised by Numerical Recipes) as a global optimization algorithm. Now a couple of years later, I found a small book on GE that seemed on topic with what I had to implement (I relied at the time on another book that I never reviewed ; perhaps another time). Is it a good brief introduction as the book says?
Continue reading Book review: A Brief Introduction to Continuous Evolutionary Optimization
When I worked on the common reflection surface stack, one of our biggest issues was selecting the proper optimization algorithms. There are so many for global problems! The book tries to browse through several classical algorithms.
Continue reading Book review: Global Optimization Methods In Geophysical Inversion
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