PythonFlaskScikit-learnStreamlitAI / ML
EasyML — No-Code Machine Learning Platform
A no-code ML platform that democratises machine learning — upload a dataset, get model recommendations, run predictions, and download trained models. No coding required.
AI-Readable Summary
EasyML — No-Code Machine Learning Platform is a project by Amal Anilkumar. It focuses on software product development using a modern TypeScript stack. This page documents the build context, technical approach, and outcome.
Jun 2026
Overview
EasyML makes machine learning accessible to anyone — business analysts, researchers, and domain experts — without requiring a single line of Python. Upload your data, choose your goal, and let the platform handle the rest.
How It Works
- Upload your dataset — CSV, Excel, or JSON
- Auto-preprocessing — EasyML handles missing values, encoding, and normalisation automatically
- Model recommendation — the platform evaluates multiple algorithms and recommends the best fit
- Train & evaluate — see accuracy metrics, feature importance, and model diagnostics
- Make predictions — input new data and get instant predictions
- Download your model — export the trained model for integration into other systems
Supported Tasks
- Classification — spam detection, customer churn, disease diagnosis, sentiment analysis
- Regression — price prediction, demand forecasting, performance estimation
Tech Stack
- Python — core ML processing
- Scikit-learn — model training, evaluation, AutoML pipeline
- Streamlit — interactive web interface (no frontend framework needed)
- Pandas / NumPy — data preprocessing and analysis
- Pickle / Joblib — model serialisation and download