🌠 Comet ML Flashcards
Track, Compare, and Optimize Machine Learning Experiments
🌟 What is Comet ML?
Comet is a platform for experiment tracking, model optimization, and collaboration in ML projects.
💾 Installation
Install using pip install comet-ml. Requires an API key to connect to your workspace.
🔐 API Key
Get your API key from your Comet dashboard and use it to authenticate via environment variables or config file.
🧪 Experiment Object
Create an experiment using Experiment() or ExistingExperiment() to log metrics and models.
📈 Logging Metrics
Use experiment.log_metric("accuracy", value) to track performance metrics over time.
📋 Logging Parameters
Track hyperparameters with experiment.log_parameter("lr", 0.001) or pass dictionaries.
📎 Logging Artifacts
Save models, datasets, configs using experiment.log_model() or log_asset().
📊 Dashboard View
Compare experiments, visualize learning curves, parameters, and distributions in the Comet web UI.
🎯 Autologging
Comet can automatically log models, metrics, and plots for frameworks like Keras, PyTorch, XGBoost, etc.
👥 Team Collaboration
Share experiments, create reports, and collaborate in real-time with team members.
🔄 Experiment Versioning
Track code changes, environment versions, and experiment lineage using Git integration and metadata.
📌 Use Cases
Perfect for A/B testing, hyperparameter optimization, reproducible research, and MLOps workflows.