🤗 Transformers: the model-definition framework for state-of-the-art machine learning models in text, vision, audio, and multimodal models, for both inference and training.

A curated list of awesome Machine Learning frameworks, libraries and software.

scikit-learn: machine learning in Python

Deep Learning for humans

Transfer learning / domain adaptation / domain generalization / multi-task learning etc. Papers, codes, datasets, applications, tutorials.-迁移学习

A curated list of awesome mathematics resources

A Python Library for Outlier and Anomaly Detection, Integrating Classical and Deep Learning Techniques

Anomaly detection related books, papers, videos, and toolboxes

Faster R-CNN (Python implementation) -- see https://github.com/ShaoqingRen/faster_rcnn for the official MATLAB version

中文文本分类，TextCNN，TextRNN，FastText，TextRCNN，BiLSTM_Attention，DPCNN，Transformer，基于pytorch，开箱即用。

使用Bert，ERNIE，进行中文文本分类

System for AI Education Resource.

Tensorflow Faster RCNN for Object Detection

Faster-RCNN in Tensorflow

A machine learning toolkit for log parsing [ICSE'19, DSN'16]

Anomaly Detection and Correlation library

About Code release for "Anomaly Transformer: Time Series Anomaly Detection with Association Discrepancy" (ICLR 2022 Spotlight), https://openreview.net/forum?id=LzQQ89U1qm_

Deep Learning models for network traffic classification

Implementation of TimeSformer from Facebook AI, a pure attention-based solution for video classification

FFA-Net: Feature Fusion Attention Network for Single Image Dehazing

Deep learning-based outlier/anomaly detection

WWW 2018: Unsupervised Anomaly Detection via Variational Auto-Encoder for Seasonal KPIs in Web Applications

Ensemble learning related books, papers, videos, and toolboxes

SR-CNN

Source code from the NeurIPS 2019 workshop article "Keep It Simple: Graph Autoencoders Without Graph Convolutional Networks" (G. Salha, R. Hennequin, M. Vazirgiannis) + k-core framework implementat…

WALB is raspberry Pi and HackRF based Wireless Attack LaunchBox.

第三届阿里云算法赛_i_hate_mcdonalds团队_解决方案

Code for the paper "On the Minimal Supervision for Training Any Binary Classifier from Only Unlabeled Data".

A PyTorch implementation of various Online & Stochastic optimization algorithms for deep learning

Surface exploration, resource detection and collision based on Multi-agent cooperative learning