ANNdotNET -- deep learning tool on .NET Platform
This tool addresses the problem of deep learning accessibility for engineers unfamiliar with programming languages, though it is incremental as it builds on existing frameworks like CNTK.
The authors tackled the challenge of making deep learning more accessible by developing ANNdotNET, an open-source tool on the .NET Platform that enables users to visually design, train, and evaluate deep learning models without extensive coding, resulting in a system that supports GPU training and rich performance analysis.
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.