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A model building, training and analytics dashboard focused on explainable AI for the Bosch AI hackathon at Inter IIT techmeet 2021

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An end to end model building, training and analytics dashboard with a focus on model explainability on the german trafic sign dataset.

React-Flask Based ML Web Application



Our Web Application

Explainable AI

GradCam Technique for identifying mislabelled hotspots


TSNE plots to visualize and evaluate model performance


Key Features

  • Create a complex Dataset
  • Train additional images on the fly
  • View model performances across different metrics
  • Visualize model performance
  • Get suggestions to various shortcomings in model training
  • An explainable AI-based solution to comprehend network failures

Prerequisites

  1. Git.
  2. Node & npm (version 12 or greater).
  3. A fork of the repo.
  4. Python3 environment to install flask

Directory Structure

The following is a high-level overview of relevant files and folders.

backend/
├── backend/
│   ├── template/
│   └── app.py

└── frontend/
    ├── public/
    │   ├── index.html
    │   └── ...
    ├── images/
    │   └── logo.png
    ├── src/
    │   ├── assets/
    │   │   ├── css
    │   │   └── fonts...
    │   ├── components/
    │   │   ├── Sidebar 
    │   │   └── Navbars
    │   └── views/
 
         ├── routes.js
         ├── package.json
       ├── local_vm.sh
       └── .gitignore
       

Installation

Clone

  • Clone this repo to your local machine using https://github.com/kousikr26/ml-dashboard/

Steps to run backend

In order to install all packages follow the steps below:

  1. Download the static folder from this drive: https://drive.google.com/file/d/149fh2lq7fT35RQVP5rmTgUfcYPorE9kX/view
  2. Put it in the backend/
  3. Move to backend folder
  4. For installing virtual environment - python3 -m pip install --user virtualenv
  5. Create A Virtual env - python3 -m venv env
  6. Activate virtual env - source env/bin/activate
  7. pip3 install -r requirements.txt
  8. flask run

Steps To Set Up Frontend

  1. Move to frontend folder
  2. npm install
  3. npm start

The model will be served on http://127.0.0.1:5000/


License

This project is licensed under the Apache License, Version 2.0.

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A model building, training and analytics dashboard focused on explainable AI for the Bosch AI hackathon at Inter IIT techmeet 2021

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