This application allows new neural network developers to play around with network architecture and to train/run neural network. Built from scratch, this beginning neural network utilizes a sigmoid activator function and stochastic gradient descent. The UI of the neural network allows users to customzie the architecture of a neural network without ever touching the code behind a neural work or attemping to omptimize layer usage and other critical features of a neural network that affect the effectiveness of a neural network.
bandicam.2021-05-01.23-30-14-762_Trim.mp4
- clang
- cmake
- cinder
- Visual Studio 2017+
- Download Cinder (latest version)
- Create a new project within the Cinder directory
Key | Action |
---|---|
Right arrow | Adds a layer to the end |
Left arrow | Removes a layer from the end |
Up arrow | Adds a neuron to the last layer |
Down arrow | Removes a neuron from the last layer |
The file drop event is meant to receive a text file with training or predict data. You must drop Training Data in before you can use predict features!
- Key represents the text at the top of the text file
Key | Action |
---|---|
TRAIN | Trains the neural network with the file data |
PREDICT | Predicts the data and displays the neural network output layer values in the outpout neruon |
TRAIN
EXPECTED_VALUE_1 VALUE_1 VALUE_2 ...
EXPECTED VALUE_2 VALUE_1 VALUE_2 ...
.
.
.
PREDICT
VALUE_1 VALUE_2 ...
This application was developed by Amit Sawhney. Last updated May 2021.