Popular GitHub Repositories for Data Mining

Ready-to-use OCR with 80+ supported languages and all popular writing scripts including Latin, Chinese, Arabic, Devanagari, Cyrillic and etc.

Machine Learning From Scratch. Bare bones NumPy implementations of machine learning models and algorithms with a focus on accessibility. Aims to cover everything from linear regression to deep learning.

A fast, distributed, high performance gradient boosting (GBT, GBDT, GBRT, GBM or MART) framework based on decision tree algorithms, used for ranking, classification and many other machine learning tasks.

The "Python Machine Learning (1st edition)" book code repository and info resource

Anomaly detection related books, papers, videos, and toolboxes

A fast, scalable, high performance Gradient Boosting on Decision Trees library, used for ranking, classification, regression and other machine learning tasks for Python, R, Java, C++. Supports computation on CPU and GPU.

:octocat: Machine Learning for Cyber Security

A library of extension and helper modules for Python's data analysis and machine learning libraries.

Research and development (R&D) is crucial for the enhancement of industrial productivity, especially in the AI era, where the core aspects of R&D are mainly focused on data and models. We are committed to automating these high-value generic R&D processes through our open source R&D automation tool RD-Agent, which lets AI drive data-driven AI.

List of tools & datasets for anomaly detection on time-series data.

Computer vision assisted tool to extract numerical data from plot images.

novel deep learning research works with PaddlePaddle

安全场景、基于AI的安全算法和安全数据分析业界实践

:memo: Подборка ресурсов по машинному обучению

Pytorch Repo for DeepGCNs (ICCV'2019 Oral, TPAMI'2021), DeeperGCN (arXiv'2020) and GNN1000(ICML'2021): https://www.deepgcns.org

Official Implement of "ADBench: Anomaly Detection Benchmark", NeurIPS 2022.

A curated list of adversarial attacks and defenses papers on graph-structured data.

:video_game: A curated list of awesome game datasets, and tools to artificial intelligence in games

Feature engineering is the process of using domain knowledge to extract features from raw data via data mining techniques. These features can be used to improve the performance of machine learning algorithms. Feature engineering can be considered as applied machine learning itself.

(AAAI' 20) A Python Toolbox for Machine Learning Model Combination