Learning about Learning - Part 1

The plan for the next few weeks is to develop a deep understanding about machine learning and statistics. Even though I have used and applied machine learning to many projects, and have taken a number of offline and online courses on machine learning, I feel like I don’t have a visceral understanding of it and have barely scratched the surface. My goal is to have a strong theoretical foundation and avoid the “throw things at it and see what sticks” approach.

Stage 1: Build a strong mathematical foundation, be able to reason about probability from a measure theoretic perspective and fill in holes in math. The plan of attack is:

I will write more about Stage 2 in a future blog post and about tactics/lessons about effectively learning this material, provided I am able to get through it in a reasonable amount of time.

 
6
Kudos
 
6
Kudos

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An algorithm for trending topics

In this post I will describe a really simple algorithm for identifying trending items or posts in your application. TF - IDF (term frequency, inverse document frequency) is a technique that was used to rank search results in early search... Continue →