ML Simulator

Built During Hack-A-BIT 2.0

IDEA ABSTRACT: A machineLearning playground/simulator where one can analyze different datasets graphically and statistically and apply various classification and regression models. It will be capable of determining the best suitable algorithm for any case and applying it. One may also select the preferred algorithm for predictions and compare the efficiencies of different algorithms. Theidea is simple, you have a dataset but don't have knowledge about models, also doesn't care how to do the stuff but is only concerned about the results. Don't worry we have got the solution, upload your models and we will run through our black box formula and give you the best of the results which would take hours of human efforts.

Tech Stack: ReactJs(Frontend), Flask (Backend), Python Libraries (SKlearn, Pandas, Numpy, NLTK,Spacy), GIT

How To Use Our Platform

1. Clone the repo https://github.com/hackabit19/skilled_Noobs.git.
2. Change the directory

    $ cd skilled_Noobs

3. Run the command

    $ pip install -r requirements.txt

3. Start the server

$ flask run

Walkthrough

1. Click on the choose file on the top to upload the dataset
2. Click Upload to visualise the dataset.
3. Also, switch tables to get a in-depth picture of the dataset.

NOTE: We have, our train.csv file for the demo purpose.

Contributors

Built with 💜 by team skilled_Noobs

1. Harshit Singh
2. Aayushi Dwivedi
3. Rithik Sharma