Where do I start?

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.

My Plan:

Core workout – back to basics:

Review Linear Algebra, Probability theory, Linear Optimization and Calculus.  Learn about Convex Optimization

Mass building:

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

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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

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