CSVToML

CSVtoML is a service to convert your csv file to a ML model Powered by

CSVtoML is a cloud-based, mobile-ready, Streamlit-powered application to let you convert your csv file to ML model and tune the hyperparameters too.

• The app uses streamlit as frontend
• Scikit Learn in the Backend

Link to the app

https://csvtoml.azurewebsites.net/

Features

• Import a CSV file and watch it magically convert to ML Model
• Choose the Best Model for your data
• Works for both classification and reression problems
• Select the hyperparameters search range and get the best hyperparamreters
• Use the generated model to predict the results

Any suggestions are welocme you can contact me [Kuljot Singh] on my email [kuljotme035@gmail.com][df1]

There is one known issue causing the number of columns to change due to streamlit's behavior of running the entire app from starting upon interaction with buttons !Please press [R] on the keyboard or press button And it will resolve

Tech

CSVtoML uses a number of open source libraries to work :

• Streamlit - For frontend of the web apps!
• SciKit Learn - Make and train the ML models
• XGBOOST - A great ensemble type ML model as an option
• Numpy - for numerical processing
• Pandas - handeling the dataframes

And CSVtoML itself is open source with a [https://github.com/Kuljot/csv_hypertuner][dill] on GitHub. Built as an educational project. Please treat it for educational purpose only, PLEASE DONT UPLOAD ANY SENSITIVE/PERSONAL INFO.

Installation on your local Machine

CSVtoML requires Python 3.11+ to run.

Clone the repository on your device

git clone https://github.com/Kuljot/csv_hypertuner.git
cd csv_hypertuner

Create a virtual environment and activate it

sudo apt install python3.11-venv
python3.11 -m venv env
source env/bin/activate

Install the requirements

pip install -r requirements.txt

Run the application

streamlit run app.py

Docker

CSVtoML can be containerized via docker.

By default, the Docker will expose port 8080 but streamlit uses 8051, so in the Dockerfile I have exposed 8051 explicitly. Simply use the Dockerfile to build the image.

sudo docker build -t csvtoml .

Verify the app by navigating to your server address in your preferred browser.

http://localhost:8501/

License

CC OpenSource!