Keepsake

Keepsake

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Ray

Ray

Anyscale
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+

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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.

About

Develop on your laptop and then scale the same Python code elastically across hundreds of nodes or GPUs on any cloud, with no changes. Ray translates existing Python concepts to the distributed setting, allowing any serial application to be easily parallelized with minimal code changes. Easily scale compute-heavy machine learning workloads like deep learning, model serving, and hyperparameter tuning with a strong ecosystem of distributed libraries. Scale existing workloads (for eg. Pytorch) on Ray with minimal effort by tapping into integrations. Native Ray libraries, such as Ray Tune and Ray Serve, lower the effort to scale the most compute-intensive machine learning workloads, such as hyperparameter tuning, training deep learning models, and reinforcement learning. For example, get started with distributed hyperparameter tuning in just 10 lines of code. Creating distributed apps is hard. Ray handles all aspects of distributed execution.

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Audience

Developers in need of a tool to manage their code and enhance the efficiency of their workflows

Audience

ML and AI Engineers, Software Developers

Support

Phone Support
24/7 Live Support
Online

Support

Phone Support
24/7 Live Support
Online

API

Offers API

API

Offers API

Screenshots and Videos

Screenshots and Videos

Pricing

Free
Free Version
Free Trial

Pricing

Free
Free Version
Free Trial

Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

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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
Webinars
Live Online
In Person

Training

Documentation
Webinars
Live Online
In Person

Company Information

Replicate
United States
keepsake.ai/

Company Information

Anyscale
Founded: 2019
United States
ray.io

Alternatives

Alternatives

TensorBoard

TensorBoard

Tensorflow
Keepsake

Keepsake

Replicate

Categories

Categories

Integrations

PyTorch
Python
TensorFlow
Amazon EC2 Trn2 Instances
Amazon EKS
Amazon S3
Amazon Web Services (AWS)
Apache Airflow
Azure Kubernetes Service (AKS)
Dask
Databricks Data Intelligence Platform
Flyte
Google Cloud Platform
Google Cloud Storage
JSON
Kubernetes
LanceDB
Snowflake
Union Cloud
scikit-learn

Integrations

PyTorch
Python
TensorFlow
Amazon EC2 Trn2 Instances
Amazon EKS
Amazon S3
Amazon Web Services (AWS)
Apache Airflow
Azure Kubernetes Service (AKS)
Dask
Databricks Data Intelligence Platform
Flyte
Google Cloud Platform
Google Cloud Storage
JSON
Kubernetes
LanceDB
Snowflake
Union Cloud
scikit-learn
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