Try every ML algorithm

We as a Data Scientist are very lazy in trying out every different algorithm on a given dataset.

This web interface provides you a convinent way of switching between algorithms are seeing there results. With this now, you can apply machine learning models without writing a Single Piece of code.

The web application is written in streamlit.

Link to the web app is here

How it works

• Open the App
• Upload the dataset*
• Inspect your data, if you wish
• Select the features
• Select the label
• Make a Train Test split
• Select an appropriate algorithm
• Start tweaking the hyperparameters

This app expects a preprocessed dataset with all the NaN, Null values handled properly, One Hot encoded, and scaled

Demo

Required Modules

• Pandas
• Streamlit
• Scikit-learn

Getting a copy of this repo

Clone the repository before running any commands

$ git clone https://github.com/AnuragAnalog/Try-every-ML-algorithm.git
$ cd Try-every-ML-algorithm

Installation

Run the below command to install all the dependencies in your local machine to run the py script.

$ sudo pip3 install -r requirements.txt

Running the app

$ streamlit run app.py

Algorithms

• Regression

  • Linear Regression
  • K Nearest Neighbours
  • Decision Trees
  • Random Forest
  • Ada Boost
  • Gradient Boosting

• Classification

  • Logistic Regression
  • K Nearest Neighbours
  • Decision Trees
  • Random Forest
  • Ada Boost
  • Gradient Boosting

Want to contribute? then fork, develop, and create a pull-request

Future Work

• Add an option to show the code which implements the above selected algorithm with the corresponding hyperparameters.
• Added code for One Hotencoding.
• Add more algorithms.
• Add some functionality for preprocessing data too.