theanasuddin/Deep-Learning-Fundamentals
Python implementations of deep learning fundamentals, from multilayer perceptrons to CNNs, RNNs, attention mechanisms, and Transformers. Includes weekly exercises covering training algorithms, gradient descent, generative modeling, and modern neural architectures.
Stars
—
Forks
—
Language
Jupyter Notebook
License
MIT
Category
Last pushed
Feb 27, 2026
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/transformers/theanasuddin/Deep-Learning-Fundamentals"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
SwanHubX/SwanLab
⚡️SwanLab - an open-source, modern-design AI training tracking and visualization tool. Supports...
mdsrqbl/omnihuman
AI model that understands text & humanoids.
stas00/ml-engineering
Machine Learning Engineering Open Book
analyticalrohit/AI-ML-Cheatsheets
All Stanford Cheatsheets: Artificial Intelligence, Transformers, LLMs, Deep Learning, Machine...
avikumart/LLM-GenAI-Transformers-Notebooks
An repository containing all the LLM notebooks with tutorial and projects