There are lots of resources out there to learn machine learning: relatively unknown online academies, seminars, books, Youtube videos. I have felt quite overwhelmed and after a few months of online browsing and few frustrated hours, I have compiled notes from the three sources below to draft my self-learning plan. I will update you as I go along.
Core workout – back to basics:
Review Linear Algebra, Probability theory, Linear Optimization and Calculus. Learn about Convex Optimization
Improve algorithm design and problem solving skills (applied linear algebra)
Improve programming skills: learn python, R, Weka, Scala and LibSVM (in that order). Tune up Matlab and Octave skills
Strengthening and maintenance:
Do competitions (Kaggle and Crowdanalytix) or consulting/volunteering work to apply knowledge on as many datasets as possible
Sources for inspiration:
- Analytics Vidhya (interesting website, wish I had found it earlier in my quest. I also have to admit the reason I clicked on her site originally was to see if there was any link to Vidhya Balan, one of my favorite Indian actresses)
- Quora: there’s everything and anything here and believe it or not, very great tips
- Abishek Kumar: more detailed plan of study but interesting
2 thoughts on “Where do I start?”
Have you seen the online course by Andrew Ng on Machine Learning at Stanford University? It’s highly recommended (and free!). https://class.coursera.org/ml-005/lecture/preview
Thanks Stephan. Yes I have and am registered as well.