References
Artificial Neural Networks (ANNs) and Deep Learning
NYU Center for Data Science:
| Course | Material |
|---|---|
| Deep Learning - DS-GA 1008 | Spring 2020 | Summary |
Natural Language Processing
Stanford University
| Course | Material |
|---|---|
| CS224N: Natural Language Processing with Deep Learning | |
| Speech and Language Processing | |
| GloVe: Global Vectors for Word Representation | |
| Learning Visual N-Grams from Web Data |
Stanford University School of Engineering
https://github.com/jtrecenti/2025-verao-torch
Latent Space Visualisation: PCA, t-SNE, UMAP UMAP: Uniform Manifold Approximation and Projection for Dimension Reduction Visualizing Data using t-SNE How to Use t-SNE Effectively An Introduction to Variational Autoencoders Autoencoders, Unsupervised Learning, and Deep Architectures Autoencoders Generative Adversarial Networks (GANs) Generative Adversarial Networks (GANs) - Deep Learning Specialization Generative Adversarial Networks (GANs) - Paper GANs in Action: Deep learning with Generative Adversarial Networks
https://mathigon.org/timeline/shannon
DSA - Data Structures and Algorithms
TutorialsPoint - Data Structures and Algorithms
GeeksforGeeks - Data Structures and Algorithms
David Galles - Data Structure Visualizations
Antti Laaksonen - Competitive Programmer’s Handbook
Gayle Laakmann McDowell, Mike Mroczka, Aline Lerner - Beyond Cracking the Coding Interview