In this work, I aim to share the knowledge I've accumulated in the field of machine learning. In addition to providing answers, you'll find plenty of illustrations to clarify concepts. Where I've found myself unable to answer a question, I've cited references that I've used to answer. I've also included recommendations based on my own experiences in data science. I hope you will find this repository useful.
Main resources I have utilized:
My notes from my previous research: Most of my answers are coming from there.
Excellent math channel: https://www.youtube.com/@ritvikmath
In case you don't know: https://www.youtube.com/@statquest
All about convex optimization: https://www.youtube.com/playlist?list=PLXsmhnDvpjORzPelSDs0LSDrfJcqyLlZc
Linear Algebra: https://www.youtube.com/playlist?list=PLoROMvodv4rMz-WbFQtNUsUElIh2cPmN9
Machine Learning: https://www.youtube.com/watch?v=vStJoetOxJg&list=PLkDaE6sCZn6FNC6YRfRQc_FbeQrF8BwGI
Convolutional Neural Networks: https://www.youtube.com/watch?v=ArPaAX_PhIs&list=PLkDaE6sCZn6Gl29AoE31iwdVwSG-KnDzF
Deep Learning: https://www.youtube.com/watch?v=OVwEeSsSCHE&list=PLLssT5z_DsK_gyrQ_biidwvPYCRNGI3iv
Reinforcement Learning: https://spinningup.openai.com/en/latest/
ChatGPT: For correcting grammar mistakes, typos and validating my answers.
Thanks...