Stars
聚宝盆(Cornucopia): 中文金融系列开源可商用大模型，并提供一套高效轻量化的垂直领域LLM训练框架(Pretraining、SFT、RLHF、Quantize等)
整理开源的中文大语言模型，以规模较小、可私有化部署、训练成本较低的模型为主，包括底座模型，垂直领域微调及应用，数据集与教程等。
TradeMaster is an open-source platform for quantitative trading empowered by reinforcement learning 🔥 ⚡ 🌈
Paper list and datasets for industrial image anomaly/defect detection (updating). 工业异常/瑕疵检测论文及数据集检索库(持续更新)。
A repository of 60 useful data science prompts for ChatGPT
Extrapolating knowledge graphs from unstructured text using GPT-3 🕵️♂️
搜索、推荐、广告、用增等工业界实践文章收集（来源：知乎、Datafuntalk、技术公众号）
ADRepository: Real-world anomaly detection datasets, including tabular data (categorical and numerical data), time series data, graph data, image data, and video data.
A comprehensive survey on the time series domains
Materials for the Learn PyTorch for Deep Learning: Zero to Mastery course.
deep learning for image processing including classification and object-detection etc.
A codebase and a curated list of awesome deep long-tailed learning (TPAMI 2023).
A collection of papers studying/improving the expressiveness of graph neural networks (GNNs)
Awesome graph anomaly detection techniques built based on deep learning frameworks. Collections of commonly used datasets, papers as well as implementations are listed in this github repository. We…
FinRL: Financial Reinforcement Learning. 🔥
[IJCAI 2023 survey track]A curated list of resources for chemical pre-trained models
A Python-based development platform for automated trading systems - from backtesting to optimisation to livetrading.
A curated list of the latest breakthroughs in AI (in 2022) by release date with a clear video explanation, link to a more in-depth article, and code.
For beginner, this will be the best start for VAEs, GANs, and CVAE-GAN. This contains AE, DAE, VAE, GAN, CGAN, DCGAN, WGAN, WGAN-GP, VAE-GAN, CVAE-GAN. All use PyTorch.
A Python Library for Graph Outlier Detection (Anomaly Detection)
A collection of design patterns/idioms in Python
10 Weeks, 20 Lessons, Data Science for All!
PyTorch-based framework for Deep Hedging