Take advantage of Packt Publishing's Flash Sale: Head on over to packtpub.com to get the eBook version of Machine Learning for OpenCV, OpenCV with Python Blueprints, and OpenCV: Computer Vision Projects with Python for only $10 each!
Limited time only.
Scientific software is often developed by a single person, usually a graduate student or a postdoc. The code might run just fine on their own computer, but what if someone else wants to run it? More often than not, scientific code is poorly documented, might work in unexpected ways (or not at all), rely on nonexistent paths or resources, or might simply fail to reproduce what was published in the paper. To avoid many common challenges associated with scientific code, Morgan Taschuk from the Ontario Institute for Cancer Research (Toronto, Ontario, Canada) and Greg Wilson from the Software Carpentry Foundation (Austin, TX) have come up with a list of ten simple rules.
Good news: I am happy to announce that Machine Learning for OpenCV is being translated into Japanese and Korean. The titles will appear later this year. Until then, consider grabbing an English copy—and make sure you download the latest code from GitHub.
Stay tuned for more!
Michael Beyeler
Machine Learning for OpenCV
14 July 2017
Packt Publishing Ltd., London, England
Paperback: 382 pages
ISBN 978-178398028-4