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Suleka Helmini edited this page Aug 20, 2019 · 2 revisions

Welcome to the TensorMap wiki!

Tensormap is a web application that enables users to create deep learning models using a graphical interface without having to know how to code. We hope that this will help as a stepping stone to individuals who are starting to explore the deep learning paradigm.

Listed below are the main functions of Tensormap

As a part of Google Summer of Code 2019 we implemented the following features:

  • Make deep learning models with drag-and-drop elements (dense layers)
  • Upload data of CSV format and visualize the uploaded data
  • Perform data manipulations on uploaded data like:
    • Adding rows
    • Editing rows
    • Deleting rows
    • Deleting columns
    • Sorting columns
    • Filtering column data
    • Searching for data
  • Specify dataset and experiment related configurations like:
    • Features
    • Labels
    • Test percentage
    • Experiment type (Binary Classification, Multiclass Classification, Regression)
    • Number of epochs
    • Batch size
    • Loss function (Binary Crossentropy, Categorical Crossentropy, Mean Squared Error )
    • Optimizer (Adam optimization)
  • Download edited CSV
  • Download the code that was auto-generated according to the created model
  • Execute the created model and show the progress
  • Show the resultant metric values
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