Code Monkey home page Code Monkey logo

hrushikesh009 / ta-performance-ml-classifier Goto Github PK

View Code? Open in Web Editor NEW
0.0 1.0 0.0 1.16 MB

Explore TA performance with a model trained on Teaching Assistant Evaluation Dataset. Deployed as a Flask microservice, it predicts scores based on user input. Features include dataset manipulation and user authentication through JWT tokens. Build, serve, and evaluate TA performance effortlessly.

Python 6.68% HTML 0.70% Jupyter Notebook 92.62%

ta-performance-ml-classifier's Introduction

Project Overview

Purpose

This initiative focuses on evaluating Teaching Assistant (TA) performance using the Teaching Assistant Evaluation Dataset. Comprising assessments from various semesters and summer engagements, scores are categorized as "low," "medium," and "high."

Machine Learning Model

Built around the dataset, a machine learning model is created and deployed through a Flask microservice. If you are interested in going deeper into the understanding and training of the ML model, please see TA_Performance_ML_Classifier.ipynb. It offers a complete guide to training, evaluating, and fine-tuning/optimizing the ML model.

TA Evaluation

Endpoint: /home

Visit the home page, fill a basic form to evaluate TA performance. Upon form submission, receive a projected score based on provided data.

Backend Services

Endpoint: /predict_score

This endpoint processes user-submitted data before feeding it to the model. The evaluated score is displayed on the output.html page.

Microservice Endpoints

  1. /add_TA [POST]
  2. /update_ta/<int:id> [PUT]
  3. /retrieve_ta/<int:id> [GET]
  4. /delete_ta/<int:id> [DELETE]

Note: Above endpoints are JWT token-protected. Users register and generate unique tokens to access these services.

  1. /register_user - Register new user
  2. /login_user - Generate unique token for authentication

The microservice design is simple yet elegant.

Using the Project

Basics

  1. Fork/Clone
  2. Activate a virtualenv
  3. Install requirements

Set Environment Variables

Update project/server/config.py and run:

$ set APP_SETTINGS="server.config.DevelopmentConfig"

or

$ export APP_SETTINGS="project.server.config.ProductionConfig"

Create a .env file and place the SECRET_KEY:

$ SECRET_KEY="change_me"

Create Database

Create databases in mysql or your chosen database:

$ create database <Database Name>

Create tables and run migrations:

$ Set Flask_APP = manage.py
$ Flask Shell
$ From auth.models import db
$ db.create_all()

Run the Application

$ python manage.py runserver

Access the application at http://localhost:5000/

Specify a different port:

$ python manage.py runserver -h 0.0.0.0 -p 8080

Testing

Without coverage:

$ cd test
$ python test_auth.py #Authentication
$ python test.py      #Microservice to CURD TA
$ python test_config.py # Configuration 

ta-performance-ml-classifier's People

Contributors

hrushikesh009 avatar

Watchers

 avatar

Recommend Projects

  • React photo React

    A declarative, efficient, and flexible JavaScript library for building user interfaces.

  • Vue.js photo Vue.js

    ๐Ÿ–– Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.

  • Typescript photo Typescript

    TypeScript is a superset of JavaScript that compiles to clean JavaScript output.

  • TensorFlow photo TensorFlow

    An Open Source Machine Learning Framework for Everyone

  • Django photo Django

    The Web framework for perfectionists with deadlines.

  • D3 photo D3

    Bring data to life with SVG, Canvas and HTML. ๐Ÿ“Š๐Ÿ“ˆ๐ŸŽ‰

Recommend Topics

  • javascript

    JavaScript (JS) is a lightweight interpreted programming language with first-class functions.

  • web

    Some thing interesting about web. New door for the world.

  • server

    A server is a program made to process requests and deliver data to clients.

  • Machine learning

    Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.

  • Game

    Some thing interesting about game, make everyone happy.

Recommend Org

  • Facebook photo Facebook

    We are working to build community through open source technology. NB: members must have two-factor auth.

  • Microsoft photo Microsoft

    Open source projects and samples from Microsoft.

  • Google photo Google

    Google โค๏ธ Open Source for everyone.

  • D3 photo D3

    Data-Driven Documents codes.