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Open in Streamlit

Machine Learning Trial Room

An application to try different machine learning models on preprocessed data directly from the browser.

forthebadge pythonbadge

Demo

Trial.Room.App.Dashboard.mp4

📱 ML Trial Room 📉

Introduction

ML Trial Room is a streamlit application that allows you to play with machine learning models from your browser.

So if you're a data science practitioner you should definitely try it out 😉

How does it work ?

  1. 🗂️ You upload the preprocessed dataset, means dataset must be numerical and does not have NULL values.
  2. 📊 Basic Data analysis or Data Exploration.
  3. ⚙️ You select X features and Y target label for either Regression Models or Classification Models.
  4. 🤖 You select a model set its hyper-parameters. You can pick a model from many different models.
  5. 📉 The app automatically displays the following results:
    • For Classification Part
      • Train Accuracy
      • Test Accuracy
      • Confusion Matrix
      • Classification Report
      • Model Accuracy
      • Graph of Accuracy of each model Combined
    • For Regression Part
      • R2 Score
      • Mean Squared Error
      • Figure Matching the actual and predicted values
      • Graph of MSE of each model Combined

Technology Stack

  1. Python
  2. Streamlit
  3. Pandas
  4. Scikit-Learn
  5. Seaborn

How to Run

  • Clone the repository
  • Setup Virtual environment
$ python3 -m venv env
  • Activate the virtual environment
$ source env/Source/activate
  • Install dependencies using
$ pip install -r requirements.txt
  • Run Streamlit
$ streamlit run app.py

Contributions are welcome!

Feel free to open a pull request or an issue if you're thinking of a feature you'd like to see in the app.

Off the top of my head, I can think of:

  • Adding Preprocessing Part in the app, so we do not have to preprocess our dataset outside the app.
  • Adding feature engineering part

But if you've got other ideas, I will be happy to discuss them with you.

Contact

For any feedback or queries, please reach out to me at suwaidaslam@gmail.com.