At First i started with Krish Niaks ML crash course,
But is was bit High Level So, Dropped it, as it was a bit advance 😅😅
Then in sem 4 i started with ML maths with JOSH STARMER, it was good.
He wonderfully taught maths required to understand ML algorithms.
So what i did was:
- Learned the Maths for a particular Algo
- Then i implement that algorithm in python, some with sklearn and some with from scratch implementation
My Learning Partners:
- Bard
- ChatGpt
- ChatPDF
- Daniel Bourke's Github
- DataCamp😍: An amazing platform, it's super amazing, unlike Udemy with video lectures you get handson exercise during the course, Guided and Unguided Project.
But it is paid 😑...
Wait We can get it's Free 3 months Premium Access using Github student's developer pack
After finishing this algorithms, i started with Deep learning,
but before starting with what it actually is i just looked for an overview at 3Blue 1 Brown Youtube Channel.
it was good, like it make you visualize what this thing is all about.
3Blue 1Brown (Maths & Neural Nets) |
MNIST DB for Handwritten Digits (useful for Neural Nets) |
Link to what i was reading and watching for it: