This repository contains my artificial intelligence learning journey (mainly ML & DL).
All the resources mentioned in the repository are ones that I genuinely used & found them to be good quality.
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- Adam Optimizer explained (Momentum, Adagrad, Adam): https://www.youtube.com/watch?v=IWvTU6swl_E
- Momentum, Adagrad, RMS Prob & Adam explained: https://www.youtube.com/watch?v=MD2fYip6QsQ
- 16 most popular optimizers (Refresher / Covers AdamW & Yogi too): https://youtu.be/7m8f0hP8Fzo
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- watch the first 3 videos from this playlist: https://www.youtube.com/playlist?list=PLkDaE6sCZn6Hn0vK8co82zjQtt3T2Nkqc
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- intuition / simply explained: https://www.youtube.com/watch?v=EehRcPo1M-Q
- Bias and Variance (to understand the need for regularization):
- watch the first 3 videos from this playlist: https://www.youtube.com/playlist?list=PLkDaE6sCZn6Hn0vK8co82zjQtt3T2Nkqc
- L1 & L2 explained: https://youtu.be/rQVODj9YDp0
- L1 & L1 (mathematical): https://www.youtube.com/watch?v=6g0t3Phly2M
- Dropout explanation: https://youtu.be/D8PJAL-MZv8
- Why dropout works: https://youtu.be/ARq74QuavAo
- More dropout explanation: https://youtu.be/kry2JghtMSY
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- normalization & standardization explained:
- Batch normalization:
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- understanding logistic regression (lecture): https://www.youtube.com/watch?v=abB3fwfPy14
- logistic regression theory & implementation: https://www.youtube.com/watch?v=S6iuhdYsGC8
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- Tutorial for learning the basics: https://matplotlib.org/stable/tutorials/pyplot.html
- Read lifecycle of a plot: https://matplotlib.org/stable/tutorials/lifecycle.html
- Randomly read some parts from user guide (depends on your curiosity & what you want to learn)
- Read Quick start guide page to have an overview of how matplotlib works
- Read Axes introduction for an overview of how Axes work
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- pytorch crash course: https://www.youtube.com/watch?v=c36lUUr864M
- pytorch autograd explained: https://www.youtube.com/watch?v=hjnVLfvhN0Q
- 24h course: https://www.youtube.com/watch?v=Z_ikDlimN6A&t
- This is my goto resource for anything related to basics in pytorch: https://www.learnpytorch.io/
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- image processing concepts: https://www.youtube.com/playlist?list=PLcQ8H2FtZMugV6cbWfdaIgbkGZjKgOYAx
- opencv crash course: https://www.youtube.com/watch?v=oXlwWbU8l2o
- computer vision in pytorch (course): https://www.youtube.com/watch?v=Z_ikDlimN6A&t=50420s (CV section)
- Variability (range, standard deviation & variance): https://www.youtube.com/watch?v=s7WTQ0H0Acc