ANNdotNET is an open source project for deep learning written in C# with ability to create, train, evaluate and export deep learning models. The project consists of the Graphical User Interface module capable to visually prepare data, fine tune hyper-parameters, design network architecture, evaluate and test trained models. The ANNdotNET introduces the Visual Network Designer, (VND) for visually design almost any sequential deep learning network. Beside VND, ANNdotNET implements Machine Learning Engine, (MLE) based on CNTK - deep learning framework, with ability to train and evaluate models on GPU. For model evaluation ANNdotNET contains rich set of visual and descriptive performance parameters, history of the training process and set of export/deployment options. The advantage of using ANNdotNET over the classic code based ML approach is more focus on deep learning network design and training process instead of focusing on coding and debugging. It is ideal for engineers not familiar with supported programming languages. The project is hosted at github.com/bhrnjica/anndotnet.
翻译:ANNDontNET是一个开放源码项目,用于在C#中写成深层学习,有能力创建、培训、评价和输出深层学习模型,该项目包括图形用户界面模块,能够对数据进行视觉准备、微调超参数、设计网络结构、评价和测试受过训练的模式。ANNDontNET为视觉设计引入视觉网络设计器(VND),几乎可以连续进行任何深层学习网络。VND 的边缘是ANNDDONTNET 工具机器学习引擎(MLE),基于 CNTK - 深层学习框架,有能力对GPU模型进行训练和评价。模型评价ANNDondontNET包含丰富的视觉和描述性能参数、培训过程的历史以及出口/部署选项集。在基于 ML 的经典代码方法上使用ANNDONTNET的好处是更多地侧重于深层次的网络设计和培训过程,而不是侧重于编程和调试调。对于不熟悉所支持的编程语言的工程师来说,这是理想的。该项目设在 Github.com/brnjica/annotnet。