I think I watched some 5 hours of Stanford lectures on RNN for Visual Recognition and Deep learning for NLP. I'm still afraid of the math.
Also did a sort of retrospective of last 10 days of effort:
Things that I think went well:
* Sticking to the daily struggle to learn ML and related areas!
* Spending equal time on theory and coding.
* Not giving up when I don't understand a concept! Good job Harsha
Things that I think did not go well:
* Not having a defined curriculum to study. This lead to having to think "what to do today" everyday. Not cool
* Not having a fixed goal [Ex: I will learn RNN end to end OR I will learn TensorFlow API ]. This lead to lack of focus and much context switch
* Not utilising available hours to learn more. I still get distracted by twitter, youtube and reddit. Not cool.
Focus for next 10 days:
* TensorFlow API and being comfortable in implementing easy RNN / CNN / LSTM examples with TF.
* Learning basics of speech recognition : Understand MFCC, CTC and related concepts
* Getting comfortable with data pre-processing. Mostly how to use python, I think.
Alright!
Mood: Happy, focussed. [could be just caffiene high]