How did you started with machine learning? Give us your best ML, linear algebra, stats, calculus recommendations!
Are you a theory first or code first learner?
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I like the idea of top down learning and love to code first and then dive into the mathematics behind it.
Here is one of the articles I wrote for getting started in Deep learning.
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For me, I wasn’t aware of the top down approach which is really cool for me now( i wish jeremy had started fastai back in 2017, but better late than never) I started with Prof. Andrew Ng’s course on cousera which was the most popular resource available back then and then figured other resources.
My best recomendations are as follows:
- For Machine learning: CS229 by stanford University taught by Prof. Andrew Ng
- Deep Learning: Deep Learning for Coders(Part 1 and Part 2) by Jeremy Howard, CS231n by Stanford University for an extensive intro to deep learning basics and Computer Vision.
- For Linear Algebra: MIT OCW 18.06 - Linear Algebra by Prof. Gilbert Strang and 3 blue 1 brown series on Linear algebra.
- For Calculus: Single Variable Calculus and Multivariable Calculus by MIT OCW and Khan Academy’s course on calculus. 3 blue 1 brown series on calculus for Visual understanding of the concepts.
- Probability: Statistics 110: Probability by Harvard University
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Thanks for sharing!
We might have a CS231n study group happening in a few weeks if you’d like to join and revisit the course 
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Oh that’s amazing @bhutanisanyam1 I would definitely join it as I plan to revisit the concepts and blog about the topics. Definitely count me in for any volunteering as a part of the study group. Thanks for sharing this
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Wow. Hope that it will come true.
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Thanks for the interest, @md-porom004, @saiamrit.
The plan is to first host #community-events:pytorch-book so that we can also invite folks that are new to the field to learn. And then later, kickoff CS231n study group/CS224n.
Well, that’s the plan but I might start one sooner than later 
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Looking forward to learning from you @bhutanisanyam1
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I started out with an applied linear algebra course in MatLab during grad school. I then got interested in Data Mining, so I took a coursera course on Intro to Python Data Mining (or something like that).
I then went to IBM and started learning about Time Series.
I was really inspired by this article: http://www.ams.org/notices/201204/rtx120400532p.pdf
But for some reason, the very first book I tried to read on Neural Nets was this:
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Oh, I’ve never heard of this book 
Bryan, could you please recommend some resources for learning TS? 
I really like Hyndman’s book on timeseries forecasting. The intro chapters do a nice job of high level intro to all TS problems as well.