gpxlcj

AutoGPT

AutoGPT is the vision of accessible AI for everyone, to use and to build on. Our mission is to provide the tools, so that you can focus on what matters.

transformers

🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.

awesome-chatgpt-prompts

This repo includes ChatGPT prompt curation to use ChatGPT better.

gpt4all

GPT4All: Chat with Local LLMs on Any Device

DeepSpeed

DeepSpeed is a deep learning optimization library that makes distributed training and inference easy, efficient, and effective.

tuning_playbook

A playbook for systematically maximizing the performance of deep learning models.

ChatPaper

Use ChatGPT to summarize the arXiv papers. 全流程加速科研，利用chatgpt进行论文全文总结+专业翻译+润色+审稿+审稿回复

Statistical-Learning-Method_Code

手写实现李航《统计学习方法》书中全部算法

beautify-github-profile

This repository will assist you in creating a more beautiful and appealing github profile, and you will have access to a comprehensive range of tools and tutorials for beautifying your github profile. 🪄 ⭐

Book4_Power-of-Matrix

Book_4_《矩阵力量》 | 鸢尾花书：从加减乘除到机器学习；上架！

EdgeGPT

Reverse engineered API of Microsoft's Bing Chat AI

pytorch-template

PyTorch deep learning projects made easy.

filterpy

Python Kalman filtering and optimal estimation library. Implements Kalman filter, particle filter, Extended Kalman filter, Unscented Kalman filter, g-h (alpha-beta), least squares, H Infinity, smoothers, and more. Has companion book 'Kalman and Bayesian Filters in Python'.

neuralforecast

Scalable and user friendly neural :brain: forecasting algorithms.

lion-pytorch

🦁 Lion, new optimizer discovered by Google Brain using genetic algorithms that is purportedly better than Adam(w), in Pytorch

LTSF-Linear

[AAAI-23 Oral] Official implementation of the paper "Are Transformers Effective for Time Series Forecasting?"

Autoformer

About Code release for "Autoformer: Decomposition Transformers with Auto-Correlation for Long-Term Series Forecasting" (NeurIPS 2021), https://arxiv.org/abs/2106.13008

PhySO

Physical Symbolic Optimization

ideas

awesome-normalizing-flows

Awesome resources on normalizing flows.

T-GCN

Temporal Graph Convolutional Network for Urban Traffic Flow Prediction Method

OmniXAI

OmniXAI: A Library for eXplainable AI

EnergonAI

Large-scale model inference.

Awesome-time-series

A comprehensive survey on the time series domains

FOST

FOST is a general forecasting tool, which demonstrate our experience and advanced technology in practical forecasting domains, including temporal, spatial-temporal and hierarchical forecasting. Current general forecasting tools (Gluon-TS by amazon, Prophet by facebook etc.) can not process and model structural graph data, especially in spatial domains, also those tools suffer from tradeoff between usability and accuracy. To address these challenges, we design and develop FOST and aims to empower engineers and data scientists to build high-accuracy and easy-usability forecasting tools.

LargeST

LargeST: A Benchmark Dataset for Large-Scale Traffic Forecasting (NeurIPS 2023 DB Track)

pytorch_explain

PyTorch Explain: Interpretable Deep Learning in Python.

BasketTracking

Basketball 🏀 action tracking and understanding using classical computer vision approaches and deep learning.

jzperf

jzperf is a L3-L7 network load tester.

ICDM2023-Tutorial-Time-Series

ICDM’23 Tutorial, “Robust Time Series Analysis and Applications: A Interdisciplinary Approach”