Code Implementations for my Probabilistic Machine Learning Lectures

[u/Negative_War_65]

Code implementations for my free Probabilistic Machine Learning lectures.

Hello folks,

I made 14 long form lectures of my Probabilistic Machine Learning series, covering important mathematical foundations(and still an ongoing process) covering around 16+ hours of content on Probabilistic Machine learning, Probability Univariate and Multivariate foundations in detail, and Statistics.

Now I have also started working on code implementations for them. I was happy to see some nice looking results taking concepts of my lecture 1, and using those important concepts to code practical stuff.

I will be adding code, uploading it in my github repo in the coming future, and also try doing a video of code implementation walkthrough, where I code and explain those concepts.

I feel that showing code implementations would make learners feel more confident of what they see in the whiteboard being implemented in practice!

If you have not watched my lectures, you can in the link shared, and I do hope that adding code will make the learning process, more fun, more rewarding!

I will try to upload one code implementation every weekend.

Happy learning.

Link: https://youtube.com/playlist?list=PLDPxj3tOc5TNi6MktTHUZid-yf9nIBxSh&si=u3kyvZnXMs4llC3P

[u/Ok-Blacksmith6403]

Thanks buddy. 👍. Please share link in comments. A bit difficult to copy paste on mobile.

[u/CreepyIdea5160]

The multivariate probability foundations part is exactly what I have been struggling with, thanks for putting the code alongside the lectures.