About EtherML

EtherML is an end-to-end Machine Learning (ML) Model Comparison Dashboard that allows users to upload datasets, automatically train models, visualize results, compare metrics, and generate predictions — all through a clean and interactive interface powered by a scalable Application Programming Interface (API).

🧩 Problem Statement

In real-world scenarios, beginners and professionals often struggle to identify the best-performing machine learning model for a dataset. Training, comparing, and testing different models typically requires coding experience, time, and knowledge of ML concepts. Additionally, there is a lack of interactive tools that can clearly visualize model performance using metrics such as Accuracy, Precision, Recall, F1-score, and more.

🎯 Main Objective & Scope

  • Upload a CSV dataset effortlessly
  • Automatic preprocessing & cleaning
  • Train multiple machine learning models instantly
  • Compare results using key statistical metrics
  • Visualize performance through charts & tables
  • Download the highest-performing trained model
  • Perform predictions using manual feature input

🔀 System Flow Diagram (Visual Overview)

User
Next.js Frontend
FastAPI Backend
ML Models (Scikit-Learn)
Training & Evaluation
Metrics + Visualizations
Best Model Selected
Download / Make Predictions

🌍 Real-World Use Cases

  • Medical diagnosis & health risk analysis
  • Stock and financial trend predictions
  • Customer churn forecasting
  • Fraud detection & anomaly checks
  • Education, ML learning & research projects
  • Automated ML experimentation environments

🚀 Future Improvements

  • Support for advanced multi-class & multi-label datasets
  • Deep learning support (CNNs, RNNs, Transformers)
  • Drag & drop visual feature engineering
  • Automated hyper-parameter tuning (AutoML style)
  • Cloud-based deployment & model endpoints
  • User model history, version tracking & audit logs

🏗️ System Architecture

  • Frontend: Next.js + Tailwind CSS
  • Backend: FastAPI (Python)
  • ML: Scikit-Learn
  • Auth: JWT + Cookies + MongoDB
  • Charts: Chart.js

📖 Glossary

ML — Machine LearningAI — Artificial IntelligenceCSV — Comma Separated ValuesROC — Receiver Operating CharacteristicAUC — Area Under CurveTP — True PositiveTN — True NegativeFP — False PositiveFN — False Negative
© 2025 — EtherML | Crafted & Designed by Snehashish