Linear Algebra, Probability, Statistics, Calculus, and Optimization. These are the foundations behind building machine learning models.
๐๐ป ๐๐ต๐ถ๐ ๐ฎ๐ด๐ฒ ๐ผ๐ณ ๐ฐ๐ฎ๐ฝ๐๐๐น๐ฒ ๐บ๐ฎ๐ฐ๐ต๐ถ๐ป๐ฒ ๐น๐ฒ๐ฎ๐ฟ๐ป๐ถ๐ป๐ด, ๐ผ๐ป๐น๐ ๐ฑ๐ฒ๐ฒ๐ฝ, ๐ณ๐ผ๐๐ป๐ฑ๐ฎ๐๐ถ๐ผ๐ป๐ฎ๐น ๐ธ๐ป๐ผ๐๐น๐ฒ๐ฑ๐ด๐ฒ ๐๐ถ๐น๐น ๐ต๐ฒ๐น๐ฝ ๐๐ผ๐ ๐๐๐ฎ๐ป๐ฑ ๐ผ๐๐.
If you are serious about transitioning to ML, don't start with toy Kaggle projects like millions. Start by building a strong foundation.
On Vizuara's YouTube channel, I have released an entire course on "๐๐ผ๐๐ป๐ฑ๐ฎ๐๐ถ๐ผ๐ป๐ ๐ณ๐ผ๐ฟ ๐ ๐ฎ๐ฐ๐ต๐ถ๐ป๐ฒ ๐๐ฒ๐ฎ๐ฟ๐ป๐ถ๐ป๐ด" where we cover the above topics along with programming fundamentals. If you are a beginner, you can start with this. You will be already ahead of 99.9% of the people.
Here are the lectures I have published so far. More will be published on this playlist: https://lnkd.in/g2K97xHW
1) Course introduction: https://lnkd.in/gDdj2Wim
2) Linear Algebra: Vector transformation, span, and basis: https://lnkd.in/gBbrSnMd
3) Linear transformation as a matrix multiplication: https://lnkd.in/gpJTNauq
4) Product of two matrices as composite transformation: https://lnkd.in/gWb3RWsD
5) 3D linear transformation: https://lnkd.in/g94VzbeX
6) A simple physical intuition for determinants: https://lnkd.in/g_5JnYbD
7) Transformation with non-square matrices (2D to 3D): https://lnkd.in/gXS3Ggmg
8) Matrix inverses and their physical meaning in transformations: https://lnkd.in/g6pHWj-Q
9) Relation between dot product and transformations: https://lnkd.in/geEPwAbi
10) Simple intuition of eigenvalues and eigenvectors: https://lnkd.in/gg6dVPVM
11) Probability and statistics an introduction: https://lnkd.in/g-Ze6UY5
12) Introduction to conditional probability: https://lnkd.in/gJyr4yFs
13) Intuition and basics of Bayes theorem: https://lnkd.in/gvt4vTQT
14) Probability distributions: https://lnkd.in/gpS5cuPu
15) Hypothesis testing: https://lnkd.in/gUUJj8QG
Once you build a strong foundation, go ahead and start building ML models yourself.
These are 3 world-class playlists from MIT PhD Dr. Raj Abhijit Dandekar that you must follow.
1) ML teach by doing [37 lectures]: https://lnkd.in/gn2dEcE2
2) Building Neural Networks from scratch [34 lectures]: https://lnkd.in/gj8kHe2T
P.S: Want to learn about machine learning in depth without all the fluff?
Join our live bootcamp starting from January 2025: https://vizuara.ai/spit/
The instructors will be PhDs from top universities like MIT and ML industry professionals.
50+ students have already registered and we are closing registrations very soon!