machinelearning
ML framework
A cross-platform machine learning framework for .NET that enables developers to build, train, and deploy models without prior expertise in ML.
ML.NET is an open source and cross-platform machine learning framework for .NET.
9k stars
577 watching
2k forks
Language: C#
last commit: 2 months ago
Linked from 5 awesome lists
algorithmsdotnetmachine-learningml
Related projects:
Repository | Description | Stars |
---|---|---|
| A collection of samples and examples demonstrating the usage of ML.NET for machine learning tasks in .NET applications. | 4,508 |
| A platform for managing machine learning projects from inception to deployment | 19,021 |
| A toolset to convert and manage deep learning models across multiple frameworks. | 5,802 |
| Makes machine learning algorithms accessible to web developers | 6,510 |
| Teaches machine learning fundamentals and software engineering practices for building production-ready ML applications | 37,816 |
| A framework for hosting and training machine learning models on a blockchain, enabling secure sharing and prediction without requiring users to pay for data or model updates. | 559 |
| A machine learning framework for native code on Macs with support for neural networks and natural language processing. | 37 |
| A C++ machine learning library with bindings to other languages and bindings for multiple programming languages. | 5,151 |
| A .NET Standard library providing C# bindings for the Apache MXNet deep learning framework | 149 |
| An end-to-end platform for building and deploying machine learning applications | 186,822 |
| A machine learning compiler and deployment engine for large language models | 19,396 |
| A collection of code and patterns for building scalable machine learning systems using Kubernetes, TensorFlow, Kubeflow, and Argo Workflows. | 393 |
| A library for building scalable machine learning pipelines on distributed computing frameworks like Apache Spark | 5,083 |
| A collection of machine learning algorithms and tools implemented in JavaScript | 2,632 |
| Teaches practical aspects of productionizing ML services | 11,227 |