Comet vs. Keepsake Comparison


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About Manage and optimize models across the entire ML lifecycle, from experiment tracking to monitoring models in production. Achieve your goals faster with the platform built to meet the intense demands of enterprise teams deploying ML at scale. Supports your deployment strategy whether it’s private cloud, on-premise servers, or hybrid. Add two lines of code to your notebook or script and start tracking your experiments. Works wherever you run your code, with any machine learning library, and for any machine learning task. Easily compare experiments—code, hyperparameters, metrics, predictions, dependencies, system metrics, and more—to understand differences in model performance. Monitor your models during every step from training to production. Get alerts when something is amiss, and debug your models to address the issue. Increase productivity, collaboration, and visibility across all teams and stakeholders.	About Keepsake is an open-source Python library designed to provide version control for machine learning experiments and models. It enables users to automatically track code, hyperparameters, training data, model weights, metrics, and Python dependencies, ensuring that all aspects of the machine learning workflow are recorded and reproducible. Keepsake integrates seamlessly with existing workflows by requiring minimal code additions, allowing users to continue training as usual while Keepsake saves code and weights to Amazon S3 or Google Cloud Storage. This facilitates the retrieval of code and weights from any checkpoint, aiding in re-training or model deployment. Keepsake supports various machine learning frameworks, including TensorFlow, PyTorch, scikit-learn, and XGBoost, by saving files and dictionaries in a straightforward manner. It also offers features such as experiment comparison, enabling users to analyze differences in parameters, metrics, and dependencies across experiments.
Platforms Supported Windows Not Supported Mac Not Supported Linux Not Supported Cloud Supported On-Premises Supported iPhone Not Supported iPad Not Supported Android Not Supported Chromebook Not Supported	Platforms Supported Windows Not Supported Mac Not Supported Linux Not Supported Cloud Supported On-Premises Not Supported iPhone Not Supported iPad Not Supported Android Not Supported Chromebook Not Supported
Audience Meta machine learning platform designed to help AI practitioners and teams build reliable machine learning models for real-world application	Audience Developers in need of a tool to manage their code and enhance the efficiency of their workflows
Support Phone Support Not Supported 24/7 Live Support Not Supported Online Supported	Support Phone Support Not Supported 24/7 Live Support Not Supported Online Supported
API Offers API Supported	API Offers API Supported
Screenshots and Videos View more images or videos	Screenshots and Videos View more images or videos
Pricing $179 per user per month Free Version Supported Free Trial Not Supported	Pricing Free Free Version Supported Free Trial Not Supported
Reviews/Ratings Overall 0.0 / 5 ease 0.0 / 5 features 0.0 / 5 design 0.0 / 5 support 0.0 / 5 This software hasn't been reviewed yet. Be the first to provide a review: Review this Software	Reviews/Ratings Overall 0.0 / 5 ease 0.0 / 5 features 0.0 / 5 design 0.0 / 5 support 0.0 / 5 This software hasn't been reviewed yet. Be the first to provide a review: Review this Software

Training Documentation Supported Webinars Not Supported Live Online Supported In Person Not Supported	Training Documentation Supported Webinars Not Supported Live Online Not Supported In Person Not Supported
Company Information Comet Founded: 2017 United States www.comet.com	Company Information Replicate United States keepsake.ai/
Alternatives ClearML	Alternatives Azure Machine Learning Microsoft
Gemini Enterprise Agent Platform Google	TensorBoard Tensorflow
Weights & Biases	Flower
MLflow	Weights & Biases
Keepsake Replicate View All	Google Cloud Deep Learning VM Image Google View All
Categories Data Science Supported Deep Learning Supported LLM Evaluation Supported Machine Learning Supported ML Experiment Tracking Supported	Categories Machine Learning Supported ML Experiment Tracking Supported Version Control Supported
Machine Learning Features Deep Learning Supported ML Algorithm Library Supported Model Training Supported Natural Language Processing (NLP) Supported Predictive Modeling Not Supported Statistical / Mathematical Tools Not Supported Templates Not Supported Visualization Supported Show More Features Deep Learning Features Convolutional Neural Networks Not Supported Document Classification Not Supported Image Segmentation Not Supported ML Algorithm Library Supported Model Training Supported Neural Network Modeling Not Supported Self-Learning Not Supported Visualization Supported
Integrations PyTorch Supported Python Supported TensorFlow Supported Amazon S3 Not Supported Amazon SageMaker Supported Apache Spark Supported Axolotl Supported Clone Protocol Supported Flask Supported Google Cloud Storage Not Supported JSON Not Supported Microsoft Azure Supported New Relic Supported Plotly Dash Supported ScalePad Backup Radar Supported Seldon Supported Ultralytics Supported Weaviate Supported ZenML Supported lemwarm Supported Show More Integrations View All 23 Integrations	Integrations PyTorch Supported Python Supported TensorFlow Supported Amazon S3 Supported Amazon SageMaker Not Supported Apache Spark Not Supported Axolotl Not Supported Clone Protocol Not Supported Flask Not Supported Google Cloud Storage Supported JSON Supported Microsoft Azure Not Supported New Relic Not Supported Plotly Dash Not Supported ScalePad Backup Radar Not Supported Seldon Not Supported Ultralytics Not Supported Weaviate Not Supported ZenML Not Supported lemwarm Not Supported Show More Integrations View All 7 Integrations
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