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Book_7_《机器学习》 | 鸢尾花书：从加减乘除到机器学习；欢迎批评指正
MLBox is a powerful Automated Machine Learning python library.
A power-full Shapley feature selection method.
程序员在家做饭方法指南。Programmer's guide about how to cook at home (Simplified Chinese only).
A fast library for AutoML and tuning. Join our Discord: https://discord.gg/Cppx2vSPVP.
Ambro17 / loguru
Forked from Delgan/loguruPython logging made (stupidly) simple
《神经网络与深度学习》 邱锡鹏著 Neural Network and Deep Learning
LightSeq: A High Performance Library for Sequence Processing and Generation
The Triton Inference Server provides an optimized cloud and edge inferencing solution.
Serve, optimize and scale PyTorch models in production
An MLOps framework to package, deploy, monitor and manage thousands of production machine learning models
Probabilistic time series modeling in Python
🔅 Shapash: User-friendly Explainability and Interpretability to Develop Reliable and Transparent Machine Learning Models
Kats, a kit to analyze time series data, a lightweight, easy-to-use, generalizable, and extendable framework to perform time series analysis, from understanding the key statistics and characteristi…
Sequence modeling benchmarks and temporal convolutional networks
🌍 针对小白的算法训练 | 包括四部分：①.大厂面经 ②.力扣图解 ③.千本开源电子书 ④.百张技术思维导图（项目花了上百小时，希望可以点 star 支持，🌹感谢~）推荐免费ChatGPT使用网站
A large annotated semantic parsing corpus for developing natural language interfaces.
Tree LSTM implementation in PyTorch
Natural Gradient Boosting for Probabilistic Prediction
A PyTorch-based toolkit for natural language processing
The largest collection of PyTorch image encoders / backbones. Including train, eval, inference, export scripts, and pretrained weights -- ResNet, ResNeXT, EfficientNet, NFNet, Vision Transformer (V…
DoWhy is a Python library for causal inference that supports explicit modeling and testing of causal assumptions. DoWhy is based on a unified language for causal inference, combining causal graphic…
Uplift modeling and causal inference with machine learning algorithms