Determined AI vs. Keepsake Comparison


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About Distributed training without changing your model code, determined takes care of provisioning machines, networking, data loading, and fault tolerance. Our open source deep learning platform enables you to train models in hours and minutes, not days and weeks. Instead of arduous tasks like manual hyperparameter tuning, re-running faulty jobs, and worrying about hardware resources. Our distributed training implementation outperforms the industry standard, requires no code changes, and is fully integrated with our state-of-the-art training platform. With built-in experiment tracking and visualization, Determined records metrics automatically, makes your ML projects reproducible and allows your team to collaborate more easily. Your researchers will be able to build on the progress of their team and innovate in their domain, instead of fretting over errors and infrastructure.	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 Not 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 Companies looking for an open source deep learning training platform that makes building models fast and easy	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 Not Supported	API Offers API Supported
Screenshots and Videos View more images or videos	Screenshots and Videos View more images or videos
Pricing No information available. Free Version Not 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 Not Supported In Person Not Supported	Training Documentation Supported Webinars Not Supported Live Online Not Supported In Person Not Supported
Company Information Determined AI United States www.determined.ai/	Company Information Replicate United States keepsake.ai/
Alternatives Comet	Alternatives Azure Machine Learning Microsoft
Gemini Enterprise Agent Platform Google	TensorBoard Tensorflow
ClearML	Flower
Ray Anyscale	Weights & Biases
TensorFlow View All	Google Cloud Deep Learning VM Image Google View All
Categories AI Development Supported Artificial Intelligence Supported Deep Learning Supported ML Experiment Tracking Supported	Categories Machine Learning Supported ML Experiment Tracking Supported Version Control Supported

Integrations Amazon S3 Supported TensorFlow Supported Amazon SageMaker Supported Amazon Web Services (AWS) Supported Apache Airflow Supported Apache Spark Supported Google Cloud Platform Supported Google Cloud Storage Not Supported Hadoop Supported JSON Not Supported MLflow Supported Pachyderm Supported PyTorch Not Supported Python Not Supported Seldon Supported scikit-learn Not Supported Show More Integrations View All 11 Integrations	Integrations Amazon S3 Supported TensorFlow Supported Amazon SageMaker Not Supported Amazon Web Services (AWS) Not Supported Apache Airflow Not Supported Apache Spark Not Supported Google Cloud Platform Not Supported Google Cloud Storage Supported Hadoop Not Supported JSON Supported MLflow Not Supported Pachyderm Not Supported PyTorch Supported Python Supported Seldon Not Supported scikit-learn Supported Show More Integrations View All 7 Integrations
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