Stars
Course to get into Large Language Models (LLMs) with roadmaps and Colab notebooks.
Cramming the training of a (BERT-type) language model into limited compute.
A minimal PyTorch re-implementation of the OpenAI GPT (Generative Pretrained Transformer) training
Deep Reinforcement Learning methods for facilitating Automated Stock Trading
Practical Deep Reinforcement Learning Approach for Stock Trading. NeurIPS 2018 AI in Finance.
Repository to host and maintain scale-sim-v2 code
An implementation of TRPO with GAE in PyTorch
PPO, DDPG, SAC implementation on mujoco environment
A minimal codebase for PPO training on MuJoCo environments with some customization supports.
RL-Scope: Cross-Stack Profiling for Deep Reinforcement Learning Workloads
Model summary in PyTorch similar to `model.summary()` in Keras
A list of papers and datasets about point cloud analysis (processing)
Pure Python from-scratch zero-dependency implementation of Bitcoin for educational purposes
This is a complete package of recent deep learning methods for 3D point clouds in pytorch (with pretrained models).
A PyTorch implementation of Dynamic Graph CNN for Learning on Point Clouds (DGCNN)
Graph Neural Network Library for PyTorch
A list of ICs and IPs for AI, Machine Learning and Deep Learning.
This is originally a collection of papers on neural network accelerators. Now it's more like my selection of research on deep learning and computer architecture.
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Datasets, Transforms and Models specific to Computer Vision
Neural Network Distiller by Intel AI Lab: a Python package for neural network compression research. https://intellabs.github.io/distiller
A Pytorch implementation of Neural Network Compression (pruning, deep compression, channel pruning)
Learning both Weights and Connections for Efficient Neural Networks https://arxiv.org/abs/1506.02626