Yannic Kilcher
Yannic is actually one of the brightest people I’ve ever met. He is knowledgeable mostly in NLP and also knows Computer Vision and some Reinforcement Learning.
Here’s a list of videos from him which I liked a lot:
- How I Read a Paper: Facebook’s DETR (Video Tutorial) - YouTube: I recommend this one a lot. I’ve learned a lot from it.
- Machine Learning PhD Survival Guide 2021 - Advice on Topic Selection, Papers, Conferences & more - YouTube
- An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale (Paper Explained) - YouTube
- MLP-Mixer: An all-MLP Architecture for Vision (Machine Learning Research Paper Explained) - YouTube
AI Coffee Break with Letitia
She is very good at NLP and Transformers. She explains the topics passionately, so you would never be bored.
Here’s a list of videos from her which I liked:
- The Transformer neural network architecture EXPLAINED. “Attention is all you need” (NLP) - YouTube: This playlist is actually one of the best if you are starting with attention and transformers architecture.
- UMAP explained - The best dimensionality reduction - YouTube
- Adversarial Machine Learning explained - With examples. - YouTube
StatQuest with Josh Starmer
Josh Starmer simple explanations are famous. He talks mostly on general machine learning stuff especially decision trees and forests.
Recommended Stuff:
- A Gentle Introduction to Machine Learning - YouTube: His playlist on Machine learning.
- Happy Halloween (Neural Networks Are Not Scary) - YouTube: his playlist on Neural Networks.
Maziar Raissi
He is an assistant Professor of Applied Mathematics at University of Colorado Boulder.
He has a big playlist of deep learning papers. He explain interesting papers in the field one by one. The playlist is quite big, containing 500 videos. So, it will take some time to finish it all.
Applied Deep Learning - YouTube
Alfredo Canziani
He is an assistant Professor of Computer Science at New York University.
Recommended stuff:
- NYU Deep Learning Spring 2021- YouTube: I haven’t actually watched this playlists videos but I plan to watch them soon.
- Episode 1: Training a classification model on MNIST with PyTorch - YouTube: This playlist is actually from Lightning AI. You see Alfredo with William Falcon who try to teach you PyTorch Lightening a fun way.
DeepLearningAI
Who doesn’t know Andrew NG?
I think one of his great playlists is the one that he explains about MLOps. It is a pretty new concept which everybody who works in industry or want to work should know.
DVCorg - YouTube
MLOps Tutorial #1: Intro to Continuous Integration for ML - YouTube This is one of the best tutorials I’ve ever seen. It is very practical and shows how to implement an continuous integration system for Machine Learning with minimal effort.
Other People
Here, I list all other people which I haven’t really watched lots of video from. All of them make videos in AI field. They are not better or worst than above people, It is just that I haven’t really got to know them well (or they do not create regular content on Youtube).
- Andrej Karpathy - YouTube: This video is very good. It is a must for everyone who wants to understand what’s going on under the hood for neural networks. It implements a simple library called micrograd which can roughly do what pytorch does in a very simple way.
- Aladdin Persson - YouTube
- Cassie Kozyrkov - YouTube
- CodeEmporium - YouTube
- Jay Alammar - YouTube
- AI Bites - YouTube
- 1littlecoder - YouTube
- Edan Meyer - YouTube
- Volodymyr Kuleshov - YouTube
- sentdex - YouTube
- Tübingen Machine Learning - YouTube
- Alexander Amini - YouTube
- Neil Rhodes - YouTube
- Anastasia K - YouTube
- Arxiv Insights - YouTube
- Nicholas Renotte - YouTube
- Hung-yi Lee - YouTube: Chinese
Recently Found Channels
A New way to look at Math
These channels do not talk specifically about AI. Instead, they give intuitions about fundamental operations in Linear Algebra and Mathematics in general. I like them a lot.