This week I got to research Machine Learning!
I chose to follow Google’s Machine Learning Crash Course for a couple of reasons: 1) it uses Tensor Flow API without requiring me to download Tensor Flow in my machine, 2) it uses Colab notebooks , which are AWESOME and 3) it’s short but very detailed and comprehensive.
Since this was a short week, and we still consumed most of our day with meetings, I’m not even halfway through the tutorial, but I have learned so much already.
I really loved the way they introduced Machine Learning with Linear Regressions and it got me thinking, do teenagers realize they are learning a little Machine learning in 9th grade?
What if we taught students the application of what they are learning, rather than just solve for x? I realized also, that there aren’t many RET programs out there, how would a teacher know about Algebra being a cornerstone bridge to Machine Learning without a research opportunity?
Moving on.
I learned about loss, specifically L2 loss.
“Loss is the penalty for bad prediction. If a model’s prediction is perfect, loss is zero”. – Google ML Crash Course
L2 Loss Formula
This week we also got to hear from two speakers: Grad student Yongyi Zhao and Senior Research Engineer, Arun Ahuja.
Arun talked about the work at Deep Mind and how they are applying Deep Learning in Games. All this work and research is truly fascinating and I look forward to diving more into Machine Learning Next week.
For now, we will take a little break for the 4th of July!