SciSharp STACK's repositories
TensorFlow.NET
.NET Standard bindings for Google's TensorFlow for developing, training and deploying Machine Learning models in C# and F#.
LLamaSharp
A C#/.NET library to run LLM (🦙LLaMA/LLaVA) on your local device efficiently.
Pandas.NET
Pandas port for C# and F#, data analysis tool, process multi-dim array in DataFrame.
SciSharp-Stack-Examples
Practical examples written in SciSharp's machine learning libraries
ICSharpCore
Jupyter kernel in C# .NET Core which is the standard interface for SciSharp STACK.
Tensor.NET
A lightweight and high-performance tensor library which provides numpy-like operations but .NET style interfaces. It supports generic tensor, Linq, C# native slices and so on. (Qushui student project))
BotSharp-UI
Build, test and manage your AI Agents in the central place.
dotnet-mysql-replication
C# Implementation of MySQL replication client
CodeMinion
A code generator framework capable of auto-generating the APIs of several SciSharp libraries.
SciSharp.Models
Image Classification, Time Series, Transformer, Object Detection
Microcharts.Matplotlib
Microcharts.Matplotlib is a wrapper of Microcharts for Data Science and Machine Learning
protobuf.Text
Text format support for protobuf
tensorflow-net-docs
Tensorflow.NET documentation
Seq2SeqSharp
Seq2SeqSharp is a tensor based fast & flexible encoder-decoder deep neural network framework written by .NET (C#). It has many highlighted features, such as automatic differentiation, many different types of encoders/decoders(Transformer, LSTM, BiLSTM and so on), multi-GPUs supported and so on.
TensorFlow.NET.OpencvAdapter
A library which enables using tensorflow.net with opencvsharp. It reuses the memory to provide a good performance.
qdrant-csharp
Qdrant .NET Client
TensorDebuggerVisualizers
The Sheet Viewer, which provides instant view of the contents of the sheet when debugging.
chatbot-ui
An open source ChatGPT UI.
tensorflow
An Open Source Machine Learning Framework for Everyone
pyspark-tutorial
PySpark-Tutorial provides basic algorithms using PySpark