Implementations of basic RL algorithms with minimal lines of codes! (pytorch based)

Basic Utilities for PyTorch Natural Language Processing (NLP)

Deep-learning by using Pytorch. Basic nns like Logistic, CNN, RNN, LSTM and some examples are implemented by complex model.

🔥🌟《Machine Learning 格物志》: ML + DL + RL basic codes and notes by sklearn, PyTorch, TensorFlow, Keras & the most important, from scratch!💪 This repository is ALL You Need!

PyTorch implementation of DeepDream algorithm (Mordvintsev et al.). Additionally I've included playground.py to help you better understand basic concepts behind the algo.

PyTorch 101 series covering everything from the basic building blocks all the way to building custom architectures.

Basic versions of agents from Spinning Up in Deep RL written in PyTorch

A basic PyTorch implementation of 'Denoising Diffusion Probabilistic Models'

Basic LRP implementation in PyTorch

Basic implementation of ResNet 50, 101, 152 in PyTorch

Basic pytorch implementation of NAC/NALU from Neural Arithmetic Logic Units paper by trask et.al

A basic implementation of Layer-wise Relevance Propagation (LRP) in PyTorch.

Basic implementation of physics-informed neural network with pytorch.

pytorch implementation of basic kmeans algorithm(lloyd method with forgy initialization) with gpu support

A relatively basic implementation of RWKV in Rust written by someone with very little math and ML knowledge. Supports 32, 8 and 4 bit evaluation. It can also directly load PyTorch RWKV models.

A simple yet strong implementation of neural machine translation in pytorch

Script for converting the pretrained VGGish model provided with AudioSet from TensorFlow to PyTorch, along with a basic smoke test.

Simple Pytorch implementations of most used Generative Adversarial Network (GAN) varieties.

This repository provides tutorial for deep learning researchers and PyTorch beginners to learn and practice PyTorch.

A basic framework for your PyTorch projects

最入门的神经网络示例代码,pytorch版

Unofficial PyTorch code for BasicVSR

several basic neural networks[mlp, autoencoder, CNNs, recurrentNN, recursiveNN] implements under several NN frameworks[ tensorflow, pytorch, theano, keras]

Unofficial pytorch implementation of paper: Model Inversion Attacks that Exploit Confidence Information and Basic Countermeasures

PyTorch version of Spotify's Basic Pitch

For those who already have some basic idea about deep learning, and preferably are familiar with PyTorch.

This Guidance demonstrates how to deploy a machine learning inference architecture on Amazon Elastic Kubernetes Service (Amazon EKS). It addresses the basic implementation requirements as well as ways you can pack thousands of unique PyTorch deep learning (DL) models into a scalable architecture and evaluate performance

Some Basic PyTorch Practice

Basic implementation of BERT and Transformer in Pytorch in one short python file (also includes "predict next word" GPT task)

A basic and simple training framework for pytorch. Easy to expand for multi network interaction.