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ML.NET

Machine Learning at Microsoft with ML.NET paper
https://arxiv.org/pdf/1905.05715.pdf

https://github.com/dotnet/machinelearning

High performance and accuracy

Training on ~900 MB of an Amazon review dataset, ML.NET produced a model with 93% accuracy, scikit-learn with 92%, and H2O with 85%. ML.NET took 11 minutes to train and test the model, scikit-learn took 66 minutes, and H2O took 105 minutes.

NimbusML

https://github.com/Microsoft/NimbusML

nimbusml is a Python module that provides Python bindings for ML.NET.

Infer.NET

https://github.com/dotnet/infer
是一个在概率图模型(graphical models)中运行贝叶斯推理(Bayesian inference)的框架

　　　　

AForge.NET

https://github.com/andrewkirillov/AForge.NET

AForge.NET是一个专门为开发者和研究者基于C#框架设计的，他包括计算机视觉与人工智能，图像处理，神经网络，遗传算法，机器学习，模糊系统，机器人控制等领域。这个框架由一系列的类库组成。主要包括有：

AForge.Imaging —— 一些日常的图像处理和过滤器
AForge.Vision —— 计算机视觉应用类库
AForge.Neuro —— 神经网络计算库AForge.Genetic -进化算法编程库
AForge.MachineLearning —— 机器学习类库
AForge.Robotics —— 提供一些机器学习的工具类库
AForge.Video —— 一系列的视频处理类库
AForge.Fuzzy —— 模糊推理系统类库
AForge.Controls—— 图像，三维，图表显示控件

Accord.NET

https://github.com/accord-net/framework
Accord.NET Framework是在AForge.NET基础上封装和进一步开发来的。功能也很强大，因为AForge.NET更注重与一些底层和广度，而Accord.NET Framework更注重与机器学习这个专业，在其基础上提供了更多统计分析和处理函数，包括图像处理和计算机视觉算法，所以侧重点不同，但都非常有用。

绑定

https://github.com/SciSharp/TensorFlow.NET

https://github.com/migueldeicaza/TensorFlowSharp

https://github.com/SciSharp/Torch.NET

https://github.com/xamarin/TorchSharp

https://github.com/tech-quantum/MxNet.Sharp

https://github.com/SciSharp/Keras.NET

https://github.com/SciSharp/SharpCV

https://github.com/shimat/opencvsharp

SciSharp其它生态

https://github.com/SciSharp/NumSharp

https://github.com/SciSharp/Plot.NET

https://github.com/SciSharp/Pandas.NET

https://github.com/SciSharp/PillowSharp

https://github.com/SciSharp/Matplotlib.Net

https://github.com/SciSharp/Gym.NET

其它机器学习库

https://github.com/sethjuarez/numl

http://www.alglib.net/

https://github.com/mdabros/SharpLearning

https://github.com/jdermody/brightwire

Spark绑定

https://github.com/dotnet/spark

自动驾驶仿真器

https://github.com/lgsvl/simulator

人脸识别

https://github.com/takuya-takeuchi/FaceRecognitionDotNet

OpenPose人体姿态识别

https://github.com/takuya-takeuchi/OpenPoseDotNet

神经网络

https://github.com/Sergio0694/NeuralNetwork.NET

DL

https://github.com/harujoh/KelpNet

https://github.com/kawatan/Merkurius

RNN

https://github.com/zhongkaifu/RNNSharp

NLP

https://github.com/curiosity-ai/catalyst

https://github.com/SciSharp/CherubNLP

开源.NET平台非综合类

Math.NET

Math.NET是.NET平台下最全面的数学计算组件之一，基础功能非常完善。

Adaboost算法

1.https://github.com/bgorven/Classifier

2.https://github.com/ElmerNing/Adaboost

Apriori算法

1.https://github.com/Omar-Salem/Apriori-Algorithm

2.https://github.com/simonesalvo/apriori

PageRank算法

https://github.com/archgold/pagerank

NativeBayes(朴素贝叶斯)算法

1.https://github.com/Rekin/Naive-Bayes-Classifier
2.https://github.com/ArdaXi/Bayes.NET
3.https://github.com/amrishdeep/Dragon
4.https://github.com/joelmartinez/nBayes

kmeans算法

http://visualstudiomagazine.com/articles/2013/12/01/k-means-data-clustering-using-c.aspx

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