I was reading Modern Optimization with R (Use R!) and wondering if a book like this exists in Python too? To be precise something that covers stochastic gradient descent and other advanced optimization techniques. Many thanks!
Topic books career beginner reference-request tools
Category Data Science
I found this question useful for me. Nevertheless, I agree with Erme namely you should be able to translate code written in one language to another.
Recently I've found this book and strongly recommend Algorithms for Optimization.
Algorithms are shown in Julia Code, but the syntax of this language is very simple and in many cases similar to Python.
Here can be found a short review of the mentioned book:
Try the ND Pyomo Cookbook that is a collection of notebooks showing how to use Pyomo to solve modeling and optimization problems.
You should look for this book
Pyomo — Optimization Modeling in Python
There is a tutorial Modern Optimization in Python and a corresponding video Modern Optimization in Python | SciPy 2017 Tutoria. Although they are not books, I think they may be helpful to you.
You should be able to translate code written in one language -- even pseudo-code -- to another, so I see no reason to avoid books for R. If you want one specifically for python, there's Machine Learning in Action by Peter Harrington.
One of scikit-learn's core committers is a releasing a book in October: Introduction to Machine Learning with Python: A Guide for Data Scientists.
Geeks Mental is a community that publishes articles and tutorials about Web, Android, Data Science, new techniques and Linux security.