Deep Learning
Resources here are limited to introductory notions of deep learning.
Neural Network Basics
Title | Description & Context | Source |
---|---|---|
A Visual And Interactive Look at Basic Neural Network Math | Neural networks introduction | Jay Alammar |
A Visual Explanation of Gradient Descent Methods | Visual explanations of Momentum, AdaGrad, RMSProp, Adam | towards data science |
Neural Networks from Scratch - P.1 Intro and Neuron Code | Build a neural network in raw Python | Youtube |
Essential Math for Data Science: Information Theory | Understsand Cross Entropy | hadrienj (Github) |
Why Momentum Really Works | Detailed explanation about gradient descent and momemtum | Distill |
What is backpropagation really doing? | Video about the backpropagation algorithm in detail | 3blue1brown |
Recurrent Neural Networks cheatsheet | Cheatsheet of everything related to RNNs | Stanford CS230 |
Recurrent Neural Networks (RNNs), Clearly Explained!!! | Video explaining RNNs step by step | StatQuest |
Neural Network Advanced
Title | Description & Context | Source |
---|---|---|
The illustrated Transformer | Detailed explanation of how Transformers work testing to see what happens if description is long | Jay Alammar |
Self Attention | Short video about self attention | Rasa Learning Center |