I want to learn Machine Learning concepts, understand how to apply on real cases.
There are so many sources of information, some of them with good/bad quality, some others very complex.
The questions are simple:
- when is useful to use machine learning solution?
- what is a neuronal net?
- what are the steps to build a machine learning solution?
- what are the type of algorithms you can use for specific problems?
The solution I found
- I’m doing some Skillsoft courses I have available in the company platform. These are covering the basis and now I’m jumping on specific topics. They are nice as they include examples in Python with scikit.
- Review these notes from @TessFerrandez: Notes from Coursera Deep Learning courses: https://www.slideshare.net/TessFerrandez/notes-from-coursera-deep-learning-courses-by-andrew-ng
- Watch the video from @TessFerrandez: Machine Learning for Developers. The video explains how the process of building a machine learning solution is, explained in plain English and with very nice examples easy to remind. The video helped me to link a lot of technical ideas explained in the courses with a natural flow.