So I completed Andrew’s Machine Learning course on Coursera, I wanted to start fast.a’s Pratical Deep Learning For Coders Part 1. But I just learnt jeremy is taking a new version of this class those videos will be available early next year and also the new Machine Learning for Coders is out too.
So should I do Machine Learning for Coders while waiting for the new version of the Deep Learning For Coders, or just do it now, is there any difference, what is your suggestion?
If you’re able to attend live (online) you can sign up for fastai Live and not have to wait until next year for the deep learning courses.
The ML course is sort of a different paradigm than the DL courses although it does cover some DL material; they’re deffinitely of the same teaching style and complement each other.
That said, whether or not you sign up for the new live course, you can still start off the recent MOOC to get a taste of things, it may help pick up the new material faster.
You can actually take them in parallel from my point of view. The Machine Learning part is mostly for structured data explaining you more about the algorithms and also building them from scratch. The part where Jeremy covers the data exploration teaching you about dendograms etc is really cool. This course build your skills with what is a validation set, how to get a good validation set, explaining more about trees and Random forest, performance metrics and also the most important part the ethics of Machine Learning. This helps you get a good grip over most of the Machine Learning concepts.
The Deep Learning part from my point of view wont require you to know about trees and stuff just some basic coding skills and the curiosity to learn and explore maybe. I had taken the part1 of v2 and i found it very interesting.
So from my point of view you can actually do both the courses simultaneously.