Ryukijano

audio-diffusion-pytorch

Audio generation using diffusion models, in PyTorch.

Cuda-Script

GPU and cpu testing script for virtual and local systems before prototyping for Deep Learning or Data Science

Deep_reinforcement_learning_Course

Implementations from the free course Deep Reinforcement Learning with Tensorflow and PyTorch

ml-agents

The Unity Machine Learning Agents Toolkit (ML-Agents) is an open-source project that enables games and simulations to serve as environments for training intelligent agents using deep reinforcement learning and imitation learning.

OPEN_GL_Graphics_Programming

This repository contains the OpenGL programs and builds I made.

Pytorch-Vision-Transformer

Vision Transformer implemented from scratch in Pytorch

Rust_exorcism

This repository contains all the progress and mistakes during my time learning the Rust programming language.

xla

Enabling PyTorch on Google TPU

audio-data-pytorch

A collection of useful audio datasets and transforms for PyTorch.

community-events

Place where folks can contribute to 🤗 community events

CUDA_SLI_INFERENCE

This repo conatains some pyscripts and notebooks creating while learning to train DL models on multiple GPUS in an SLI system

d2l-en

Interactive deep learning book with multi-framework code, math, and discussions. Adopted at 400 universities from 60 countries including Stanford, MIT, Harvard, and Cambridge.

DCGAN

What is a GAN? GANs are a framework for teaching a DL model to capture the training data’s distribution so we can generate new data from that same distribution. GANs were invented by Ian Goodfellow in 2014 and first described in the paper Generative Adversarial Nets. They are made of two distinct models, a generator and a discriminator. The job of the generator is to spawn ‘fake’ images that look like the training images. The job of the discriminator is to look at an image and output whether or not it is a real training image or a fake image from the generator. During training, the generator is constantly trying to outsmart the discriminator by generating better and better fakes, while the discriminator is working to become a better detective and correctly classify the real and fake images. The equilibrium of this game is when the generator is generating perfect fakes that look as if they came directly from the training data, and the discriminator is left to always guess at 50% confidence that the generator output is real or fake.

Deep_Sort

diffusers

🤗 Diffusers: State-of-the-art diffusion models for image and audio generation in PyTorch

GANATEET

Notebooks created by me while undergoing the GAN specialization from DEEPLEARNING.AI

linux

Linux kernel source tree

Live3D-v2

Neural Rendering with Attention: An Incremental Improvement for Anime Character Animation

machinelearning

All machine learning related items will be kept here

mbrl-lib

Library for Model Based RL

metrics

📊 An infographics generator with 30+ plugins and 300+ options to display stats about your GitHub account and render them as SVG, Markdown, PDF or JSON!

noreward-rl

[ICML 2017] TensorFlow code for Curiosity-driven Exploration for Deep Reinforcement Learning

pysc2

StarCraft II Learning Environment

pytorch_ignite

High-level library to help with training and evaluating neural networks in PyTorch flexibly and transparently.

pytorchvideo

A deep learning library for video understanding research.

simulate

🎢 Creating and sharing simulation environments for embodied and synthetic data research

StyleGAN2

TSP_HOPFIELD

Code for the paper titled "Solving The Travelling Salesmen Problem using HNN and HNN-SA algorithms "

UA-_RL

Reinforcement learning specialization from the University of Alberta

yolov7

Implementation of paper - YOLOv7: Trainable bag-of-freebies sets new state-of-the-art for real-time object detectors