Introduction of ANNdotNET
ANNdotNET – is an open source project for deep learning written in C# and .NET platform. The main purpose of the project is
creating and training deep learning models. The application relies on Microsoft Cognitive Toolkit, CNTK, and it is
supposed to be GUI tool for CNTK library with extensions in data preprocessing, model evaluation,
exporting and deploying. The project is hosted at http://github.com/bhrnjica/anndotnet.
The process of creating, training, evaluating and exporting models is provided from the GUI Application and does not require knowledge for supported programming languages. The ANNdotNET is ideal in several scenarios:
- more focus on network development and training process using on classic desktop approach, instead of focusing on coding,
- less time spending on debugging source code, more focusing on different configuration and parameter variants,
- ideal for engineers/users which are not familiar with programming languages,
- in case the problem requires coding custom models, or training process, ANNdotNET CMD provides high level of API for such implementation,
- all ml configurations developed with GUI tool,can be handling with CMD tool and vice versa.
There are dozens of pre-calculated projects included in the installer which can be opened from the Start page as well as from CMD tool. The annprojects are based on famous datasets from several categories: regression, binary and multi class classification problems, image classifications, times series, etc. In pre-calculated projects the user can find how to use various neural network configurations e.g. feed forward, deep neural network, LSTM recurrent nets, embedding and drop out layers. Also, each project can be modified in terms of change its network configuration, learning and training parameters, as well as create new ml configurations.
ANNdotNET is x64 Windows desktop application running on .NET Framework 4.7.2. and .NET Core 2.0. In order to run the application, the following software components need to be installed:
- Windows 10 with x64 architecture
- .NET Framework 4.7.2 +, and .NET Core 2.+
- Visual C++ 2017 version 15.4 v14.11 toolset
- Visual C++ Redistributable Packages for Visual Studio 2013
- CUDA 10 for GPU support
- cuDNN v7.4.2 (Dec 14, 2018), for CUDA 10.0
Note: The application is tested on clean Windows Pro 10 1709 build. Probably the application will run on Windows 8 and Windows 7 as well, but those systems are not tested.