It is quite amazing that we get to learn complex subjects such as Machine Learning from one of the best tech companies in the world for FREE from the comfort of our homes!
(This post is not an advertisement lol, I sometimes still can’t believe how you can learn pretty much anything you want on the internet for free!)
I’ve been meaning to start this course for a while but never got around to it. Now, I feel I have more background and a better base to understand many of the concepts covered in the Google - Machine Learning Crash Course.
Having covered Regression in my Descriptive and Predictive Analysis class @ W.P Carey, and self studied Python for a bit, the concepts seem less daunting. However, there is a fair bit of reading and active effort required to truly understand what’s going on. There is a lot of Math here, thankfully I enjoy Math more than I enjoy programming. I hope I can compensate for my shortcomings in coding skills with Math knowledge.
Topics covered so far: Supervised vs Unsupervised model, Linear regression, Mean squared errors, Reducing loss through iteration, learning rate.