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?
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.
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.
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?
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?
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.
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.
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?
Open Source software seems for the young generation as sure as the sun rises. And even if I witnessed the emergence of Open Source, I more often than not forget that there was a time when Linux didn’t exist. This recent history brought us a lot, but we may only have handpicked some of this revolution’s fruit. Eric Raymond is one of the guys behind this revolution, and he took some time to think about the changes it brought.