Build strong foundations to transition to ML
Focus on depth. Not fluff.
Linear Algebra, Probability, Statistics, Calculus, and Optimization. These are the foundations behind building machine learning models.
𝗜𝗻 𝘁𝗵𝗶𝘀 𝗮𝗴𝗲 𝗼𝗳 𝗰𝗮𝗽𝘀𝘂𝗹𝗲 𝗺𝗮𝗰𝗵𝗶𝗻𝗲 𝗹𝗲𝗮𝗿𝗻𝗶𝗻𝗴, 𝗼𝗻𝗹𝘆 𝗱𝗲𝗲𝗽, 𝗳𝗼𝘂𝗻𝗱𝗮𝘁𝗶𝗼𝗻𝗮𝗹 𝗸𝗻𝗼𝘄𝗹𝗲𝗱𝗴𝗲 𝘄𝗶𝗹𝗹 𝗵𝗲𝗹𝗽 𝘆𝗼𝘂 𝘀𝘁𝗮𝗻𝗱 𝗼𝘂𝘁.
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 "𝗙𝗼𝘂𝗻𝗱𝗮𝘁𝗶𝗼𝗻𝘀 𝗳𝗼𝗿 𝗠𝗮𝗰𝗵𝗶𝗻𝗲 𝗟𝗲𝗮𝗿𝗻𝗶𝗻𝗴" 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!