Maschinelles Lernen · GitHub

Datasets for Predictive Maintenance

User documentation for KServe.

🤖 零基础 AI 学习之路 | 30 天从小白到实战 | Python → 机器学习 → 深度学习 → Agent应用 → 项目实战 一个完整的 AI 入门教程，包含： 📚 30 天系统教程（费曼学习法·大白话讲解） 💻 9 个完整项目（图像分类·文本生成·目标检测·模型部署·AI客服·数据分析·智能投研·RAG·AutoGPT） 🎯 200+ 代码示例（可直接运行） 🆓 完全免费开源（MIT 许可证） 📖 配套教程：CSDN专栏 https://blog.csdn.net/m0_67081842 ⭐ 如果有帮助，欢迎 Star 支持！

TPP experimentation on MLIR for linear algebra

PASQA: Pitch-Accent-Focused Speech Quality Assessment Model Trained on Synthetic Speech with Accent Errors

A zero-dependency ML framework in C with a modern Python API for full control over execution and memory.

• Practical, not just educationalCapable of running modern LLM inference (e.g. Qwen3 in BF16), not just toy models.
• Small, controllable ML runtimeDesigned to stay inspectable end-to-end - no hidden execution layers or opaque backends.

A robust and efficient TinyML inference engine.

MerLin enables researchers to build, train, and benchmark photonic quantum machine learning models using familiar ML tools.

Neural Amp Modeler LV2 plugin

DeepLog: the PyTorch for neurosymbolic AI

Agent skills for Machine Learning for Algorithmic Trading: leakage-safe quant ML, backtesting, validation, and autonomous research workflows.

• Method discipline: every skill teaches a concept-first WRONG/CORRECT pattern.
• Book alignment: skills map to the chapters and case-study workflow in Machine Learning for Algorithmic Trading.

PeakPulse AI — Real-Time Financial Market Anomaly Detection & Time-Series Machine Learning Engine

a CLI utility/library for AnimateDiff stable diffusion generation

Deep learning framework for MRI reconstruction

• MRI data and sampling. Multi-coil static, dynamic, and multislice volumes; coil-sensitivity estimation; and a library of Cartesian, radial, spiral, Poisson, Gaussian, and k-t masks. A learned Adaptive Dynamic Sampler (ADS) can also choose lines or pixels under a fixed acceleration budget.
• Reconstruction models. vSHARP, RecurrentVarNet, VarNet, RIM / CIRIM, LPDNet, XPDNet, IterDualNet, ConjGradNet, Joint-ICNet, KIKI-Net, MultiDomainNet, VarSplitNet, U-Net (2D / 3D), MEDL, and transformer reconstructors (ViT, UFormer) in image or k-space.