Upload a table of training samples

+
Output sample importances (optional)

Samples are: 

Try it with example data


Generate:   

features in encoding

+
extra (variational) features
  
  

Architecture options
+
Max weights:
Max neurons:
Max layers:
Max layer skip:
Sparse weights
Include bias


Instructions: This tool builds neural networks that:
 1) extract features from data (encoder);
 2) reconstruct source data from features (decoder).

  • Upload a table* of sample source data. These examples will train the network. Specify whether each sample is a row or column in the table and click Submit.
  • The trained network opens in a new page, where you can a) run the encoder/decoder, and b) export it as computer code for use in your own programs.

* Sample table must be a fully numeric, comma-separated .csv file with no empty fields. Max allowed: 100 kB file size, 1000 rows/columns, 1 header row/column. Generation time limited to 1 sec.