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av1352/ClearML-experiment-tracking

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App README

🚀 ClearML Experiment Tracking Dashboard

Interactive ML training dashboard showcasing ClearML's auto-magical experiment tracking capabilities.

What This Does

Train a CNN on MNIST with customizable hyperparameters and watch as ClearML automatically tracks:

—📊 All metrics (loss, accuracy) in real-time
—🔧 Hyperparameters and configuration
—💾 Model weights and artifacts
—🔀 Git commit and code changes
—📦 Python environment
—💻 System resources (GPU/CPU/RAM)

The Magic: Just 2 Lines of Code

python

from clearml import Task
task = Task.init(project_name='My Project', task_name='Experiment 1')
# Everything below is now tracked automatically! ✨

Features

—Interactive UI - Configure training with sliders
—Real-time Curves - See loss/accuracy update live
—ClearML Integration - Full experiment tracking
—Reproducibility - Clone any experiment with one click

Why ClearML?

ClearML is an open-source MLOps platform that makes experiment tracking effortless. Unlike competitors (MLflow, W&B), ClearML requires zero manual logging - just initialize once and everything is tracked automatically.

Perfect for: Teams building production ML systems who need reproducibility, collaboration, and automated experiment management.

Source Code

Full implementation: GitHub Repository

Built by: Anju Vilashni Nandhakumar Contact: nandhakumar.anju@gmail.com LinkedIn: linkedin.com/in/anju-vilashni

This is a technical demonstration and is not affiliated with ClearML.