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[ECCV 2022] ByteTrack: Multi-Object Tracking by Associating Every Detection Box

🔬 A curated list of awesome LLMs & deep learning strategies & tools in financial market.

Stock AI Trader: 1-stop platform for learning, sim & live trading. Covers: stock basics, strategies, LLMs, factor mining, ML/DL/RL, graph nets, HFT, C++ deploy & JoinQuant code. 股票AI操盘手：一站式学习、模拟、实盘平台。涵盖：股票基础、策略、大模型、因子挖掘、机器学习/深度学习/强化学习、图网络、高频交易、C++部署及聚宽代码。

🎓 Sharing machine learning course / lecture notes.

ML-powered manga translator, written in Rust.

A course in reinforcement learning in the wild

Friendly machine learning for the web! 🤖

Awesome paper list with code about generative adversarial nets

🏅 Collection of Kaggle Solutions and Ideas 🏅

The GitHub repository for the paper "Informer" accepted by AAAI 2021.

Google AI 2018 BERT pytorch implementation

🧮 A collection of resources to learn mathematics for machine learning

RSTutorials: A Curated List of Must-read Papers on Recommender System.

This repository is a curated collection of links to various courses and resources about Artificial Intelligence (AI)

Transformer related optimization, including BERT, GPT

95.47% on CIFAR10 with PyTorch

A curated list of awesome self-supervised methods

A list of popular github projects related to deep learning

docTR (Document Text Recognition) - a seamless, high-performing & accessible library for OCR-related tasks powered by Deep Learning. Ongoing development and maintenance by t2k.

Natural Language Processing Best Practices & Examples

StyleTTS 2: Towards Human-Level Text-to-Speech through Style Diffusion and Adversarial Training with Large Speech Language Models

TensorFlow 2.x version's Tutorials and Examples, including CNN, RNN, GAN, Auto-Encoders, FasterRCNN, GPT, BERT examples, etc. TF 2.0版入门实例代码，实战教程。

Train and evaluate embeddings for similarity search with PyTorch. Includes contrastive losses, hard example mining, samplers, and retrieval metrics.

TensorFlow documentation

Fault-tolerant, highly scalable GPU orchestration, and a machine learning framework designed for training models with billions to trillions of parameters

Aim 💫 — An easy-to-use & supercharged open-source experiment tracker.

Hide screen when boss is approaching.

High Performance Chinese License Plate Recognition Framework.

Setup and customize deep learning environment in seconds.

A Neural Net Training Interface on TensorFlow, with focus on speed + flexibility

NanoDet-Plus⚡Super fast and lightweight anchor-free object detection model. 🔥Only 980 KB(int8) / 1.8MB (fp16) and run 97FPS on cellphone🔥

SD-Trainer. LoRA & Dreambooth training scripts & GUI use kohya-ss's trainer, for diffusion model.

XLNet: Generalized Autoregressive Pretraining for Language Understanding

AI算法岗求职攻略（涵盖准备攻略、刷题指南、内推和AI公司清单等资料）

A scikit-learn compatible neural network library that wraps PyTorch

Pytorch🍊🍉 is delicious, just eat it! 😋😋

Time series Timeseries Deep Learning Machine Learning Python Pytorch fastai | State-of-the-art Deep Learning library for Time Series and Sequences in Pytorch / fastai

Translate darknet to tensorflow. Load trained weights, retrain/fine-tune using tensorflow, export constant graph def to mobile devices

Chinese version of CLIP which achieves Chinese cross-modal retrieval and representation generation.

The Swift machine learning library.

header only, dependency-free deep learning framework in C++14

:alarm_clock: AI conference deadline countdowns

A concise but complete full-attention transformer with a set of promising experimental features from various papers

All course materials for the Zero to Mastery Deep Learning with TensorFlow course.

Gorgonia is a library that helps facilitate machine learning in Go.

A flexible framework of neural networks for deep learning

Curated list of data science interview questions and answers

Implement a reasoning LLM in PyTorch from scratch, step by step

Official implementation of DeepLabCut: Markerless pose estimation of user-defined features with deep learning for all animals incl. humans

MMdnn is a set of tools to help users inter-operate among different deep learning frameworks. E.g. model conversion and visualization. Convert models between Caffe, Keras, MXNet, Tensorflow, CNTK, PyTorch Onnx and CoreML.