12 Key Lessons from ML researchers and practitioners
▻https://hackernoon.com/12-key-lessons-from-ml-researchers-and-practitioners-3d4818a2feff?source
Machine learning algorithms come with the promise of being able to figure out how to perform important tasks by learning from data, i.e., generalizing from examples without being explicitly told what to do. This means that the higher the amount of data, the more ambtious problems can be tackled by these algorithms. However, developing successful machine learning applications requires quite some “black art” that is hard to find in text books or introductory courses on machine learning.I recently stumbled upon a great research paper by Professor Pedro Domingos that puts together lessons learned by machine learning researchers and practitioners. In this post, I am going to walkthrough those lessons with you.Get ready to learn about: pitfalls to avoid, important issues to focus on, and (...)
#machine-learning #development #best-practices #artificial-intelligence #data-science
