-
IIT KHARAGPUR
Stars
All Algorithms implemented in Python
🧑🏫 60+ Implementations/tutorials of deep learning papers with side-by-side notes 📝; including transformers (original, xl, switch, feedback, vit, ...), optimizers (adam, adabelief, sophia, ...), ga…
TradingAgents: Multi-Agents LLM Financial Trading Framework
Machine Learning From Scratch. Bare bones NumPy implementations of machine learning models and algorithms with a focus on accessibility. Aims to cover everything from linear regression to deep lear…
Interactive deep learning book with multi-framework code, math, and discussions. Adopted at 500 universities from 70 countries including Stanford, MIT, Harvard, and Cambridge.
Graph Neural Network Library for PyTorch
☁️ Build multimodal AI applications with cloud-native stack
Code samples for my book "Neural Networks and Deep Learning"
PyTorch implementations of Generative Adversarial Networks.
Python Implementation of Reinforcement Learning: An Introduction
Python package built to ease deep learning on graph, on top of existing DL frameworks.
A paper list of object detection using deep learning.
Style transfer, deep learning, feature transform
XLNet: Generalized Autoregressive Pretraining for Language Understanding
A collection of important graph embedding, classification and representation learning papers with implementations.
Deformable Convolutional Networks
3D ResNets for Action Recognition (CVPR 2018)
A comprehensive list of Deep Learning / Artificial Intelligence and Machine Learning tutorials - rapidly expanding into areas of AI/Deep Learning / Machine Vision / NLP and industry specific areas …
Simple PyTorch Tutorials Zero to ALL!
Lazy Predict help build a lot of basic models without much code and helps understand which models works better without any parameter tuning
From Images to High-Fidelity 3D Assets with Production-Ready PBR Material
Resources and Implementations of Generative Adversarial Nets: GAN, DCGAN, WGAN, CGAN, InfoGAN
Platform for designing and evaluating Graph Neural Networks (GNN)
HY-World 1.5: A Systematic Framework for Interactive World Modeling with Real-Time Latency and Geometric Consistency