astroautomata/PySR
Symbolic Learning in Python and Julia
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Symbolic Learning in Python and Julia
Lightning ⚡️ fast forecasting with statistical and econometric models.
cubestudio开源云原生一站式机器学习/深度学习/大模型AI平台/MaaS/mlops/人工智能平台/训推平台，算法全链路流程，多租户，算力租赁平台，token中转，拖拉拽任务流pipeline编排，多机多卡分布式训练，超参搜索，推理服务，VGPU虚拟化，云边端协同，边缘计算，自动化标注平台，deepseek等大模型sft微调/奖励模型/强化学习训练，vllm/ollama/mindie大模型多机推理，私有知识库llmops智能体，AI模型市场，支持国产异构算力调度,昇腾/寒武纪/海光/摩尔/沐曦等，支持ib/roce/RDMA，信创支持
Build, train, optimize, and run computer vision models locally, from raw images to live inference. Open source, optimized for Intel® XPU (CUDA also supported).
Python package for AutoML on Tabular Data with Feature Engineering, Hyper-Parameters Tuning, Explanations and Automatic Documentation
Fast and Accurate ML in 3 Lines of Code
Distributed High-Performance Symbolic Regression in Julia
开放式的缠论python实现框架，支持形态学/动力学买卖点分析计算，多级别K线联立，区间套策略，可视化绘图，多种数据接入，策略开发，交易系统对接；
SMAC3: A Versatile Bayesian Optimization Package for Hyperparameter Optimization
ZenML 🙏: One AI Platform from Pipelines to Agents. https://zenml.io.
Hyperparameter optimization and feature selection for scikit-learn using evolutionary algorithms. A modern alternative to GridSearchCV and RandomizedSearchCV.
Generative AutoML for Tabular Data
Fast and customizable framework for automatic ML model creation (AutoML)
Java and Kotlin Code samples used on cloud.google.com
Machine learning for Ruby
That's all 16 repositories in this period.
