Keepsake Description
Keepsake, an open-source Python tool, is designed to provide versioning for machine learning models and experiments. It allows users to track code, hyperparameters and training data. It also tracks metrics and Python dependencies. Keepsake integrates seamlessly into existing workflows. It requires minimal code additions and allows users to continue training while Keepsake stores code and weights in Amazon S3 or Google Cloud Storage. This allows for the retrieval and deployment of code or weights at any checkpoint. Keepsake is compatible with a variety of machine learning frameworks including TensorFlow and PyTorch. It also supports scikit-learn and XGBoost. It also has features like experiment comparison that allow users to compare parameters, metrics and dependencies between experiments.
Keepsake Alternatives
Azure DevOps Server
Integrated software delivery tools hosted on premisis allow you to share code, track work and ship software. You can use all Azure DevOps services, or only the ones that you need to enhance your existing workflows.
Azure DevOps Server, formerly known as Team Foundation Server (TFS), is a collection of software development tools that can be used together. It is hosted on-premises. Azure DevOps Server can integrate with your existing editor or IDE, allowing your cross-functional team members to work efficiently on projects of any size.
Azure DevOps Server is source code management software, and includes features such as access Controls/Permissions, bug tracking, build automation, change management, code review, collaboration, continuous integration, and version control.
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Amazon SageMaker
Amazon SageMaker, a fully managed service, provides data scientists and developers with the ability to quickly build, train, deploy, and deploy machine-learning (ML) models. SageMaker takes the hard work out of each step in the machine learning process, making it easier to create high-quality models.
Traditional ML development can be complex, costly, and iterative. This is made worse by the lack of integrated tools to support the entire machine learning workflow. It is tedious and error-prone to combine tools and workflows. SageMaker solves the problem by combining all components needed for machine learning into a single toolset. This allows models to be produced faster and with less effort. Amazon SageMaker Studio is a web-based visual interface that allows you to perform all ML development tasks. SageMaker Studio allows you to have complete control over each step and gives you visibility.
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TensorBoard
TensorBoard, TensorFlow’s comprehensive visualization toolkit, is designed to facilitate machine-learning experimentation. It allows users to track and visual metrics such as accuracy and loss, visualize the model graph, view histograms for weights, biases or other tensors over time, display embeddings in a lower-dimensional area, and display images and text. TensorBoard also offers profiling capabilities for optimizing TensorFlow programmes. These features provide a suite to help understand, debug and optimize TensorFlow, improving the machine learning workflow. To improve something in machine learning, you need to be able measure it. TensorBoard provides the measurements and visualisations required during the machine-learning workflow. It allows tracking experiment metrics, visualizing model graphs, and projecting embedded embeddings into a lower-dimensional space.
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Weights & Biases
Weights & Biases allows for experiment tracking, hyperparameter optimization and model and dataset versioning. With just 5 lines of code, you can track, compare, and visualise ML experiments. Add a few lines of code to your script and you'll be able to see live updates to your dashboard each time you train a different version of your model. Our hyperparameter search tool is scalable to a massive scale, allowing you to optimize models. Sweeps plug into your existing infrastructure and are lightweight. Save all the details of your machine learning pipeline, including data preparation, data versions, training and evaluation. It's easier than ever to share project updates.
Add experiment logging to your script in a matter of minutes. Our lightweight integration is compatible with any Python script.
W&B Weave helps developers build and iterate their AI applications with confidence.
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Pricing
Pricing Starts At:
Free
Free Version:
Yes
Company Details
Company:
Replicate
Headquarters:
United States
Website:
keepsake.ai/
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Product Details
Platforms
SaaS
Type of Training
Documentation
Customer Support
Online
Keepsake Features and Options
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