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Description

Amazon SageMaker is a comprehensive machine learning platform that integrates powerful tools for model building, training, and deployment in one cohesive environment. It combines data processing, AI model development, and collaboration features, allowing teams to streamline the development of custom AI applications. With SageMaker, users can easily access data stored across Amazon S3 data lakes and Amazon Redshift data warehouses, facilitating faster insights and AI model development. It also supports generative AI use cases, enabling users to develop and scale applications with cutting-edge AI technologies. The platform’s governance and security features ensure that data and models are handled with precision and compliance throughout the entire ML lifecycle. Furthermore, SageMaker provides a unified development studio for real-time collaboration, speeding up data discovery and model deployment.

Description

Keepsake is a Python library that is open-source and specifically designed for managing version control in machine learning experiments and models. It allows users to automatically monitor various aspects such as code, hyperparameters, training datasets, model weights, performance metrics, and Python dependencies, ensuring comprehensive documentation and reproducibility of the entire machine learning process. By requiring only minimal code changes, Keepsake easily integrates into existing workflows, permitting users to maintain their usual training routines while it automatically archives code and model weights to storage solutions like Amazon S3 or Google Cloud Storage. This capability simplifies the process of retrieving code and weights from previous checkpoints, which is beneficial for re-training or deploying models. Furthermore, Keepsake is compatible with a range of machine learning frameworks, including TensorFlow, PyTorch, scikit-learn, and XGBoost, enabling efficient saving of files and dictionaries. In addition to these features, it provides tools for experiment comparison, allowing users to assess variations in parameters, metrics, and dependencies across different experiments, enhancing the overall analysis and optimization of machine learning projects. Overall, Keepsake streamlines the experimentation process, making it easier for practitioners to manage and evolve their machine learning workflows effectively.

API Access

Has API Yes 

API Access

Has API Yes 

Screenshots View All

Screenshots View All

Integrations

Amazon Bedrock Yes 
Amazon EC2 G4 Instances Yes 
Amazon EC2 G5 Instances Yes 
Amazon EC2 Inf1 Instances Yes 
Amazon EC2 Trn1 Instances Yes 
Amazon EC2 UltraClusters Yes 
Amazon SageMaker Canvas Yes 
Amazon SageMaker Debugger Yes 
Amazon SageMaker HyperPod Yes 
Amazon SageMaker Studio Yes 
Darktrace / SECURE AI Yes 
Deeplake Yes 
Determined AI Yes 
Flyte Yes 
Galileo Yes 
Okera Yes 
OpenMetadata Yes 
Pinecone Rerank v0 Yes 
Ray Yes 
WhyLabs Yes 

Integrations

Amazon Bedrock No 
Amazon EC2 G4 Instances No 
Amazon EC2 G5 Instances No 
Amazon EC2 Inf1 Instances No 
Amazon EC2 Trn1 Instances No 
Amazon EC2 UltraClusters No 
Amazon SageMaker Canvas No 
Amazon SageMaker Debugger No 
Amazon SageMaker HyperPod No 
Amazon SageMaker Studio No 
Darktrace / SECURE AI No 
Deeplake No 
Determined AI No 
Flyte No 
Galileo No 
Okera No 
OpenMetadata No 
Pinecone Rerank v0 No 
Ray No 
WhyLabs No 

Pricing Details

Try free for two months
Free Trial Yes 
Free Version No 

Pricing Details

Free
Free Trial No 
Free Version Yes 

Deployment

Web-Based Yes 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
Linux No 
Chromebook No 

Deployment

Web-Based Yes 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
Linux No 
Chromebook No 

Customer Support

Business Hours No 
Live Rep (24/7) No 
Online Support Yes 

Customer Support

Business Hours No 
Live Rep (24/7) No 
Online Support Yes 

Types of Training

Training Docs No 
Webinars No 
Live Training (Online) Yes 
In Person No 

Types of Training

Training Docs Yes 
Webinars No 
Live Training (Online) No 
In Person No 

Vendor Details

Company Name

Amazon

Founded

1994

Country

United States

Website

aws.amazon.com/sagemaker/

Vendor Details

Company Name

Replicate

Country

United States

Website

keepsake.ai/

Product Features

Artificial Intelligence

Chatbot No 
For Healthcare No 
For Sales No 
For eCommerce No 
Image Recognition No 
Machine Learning No 
Multi-Language No 
Natural Language Processing No 
Predictive Analytics No 
Process/Workflow Automation No 
Rules-Based Automation No 
Virtual Personal Assistant (VPA) No 

Data Governance

Access Control No 
Data Discovery No 
Data Mapping No 
Data Profiling No 
Deletion Management No 
Email Management No 
Policy Management No 
Process Management No 
Roles Management No 
Storage Management No 

Data Labeling

Human-in-the-loop Yes 
Labeling Automation Yes 
Labeling Quality Yes 
Performance Tracking Yes 
Polygon, Rectangle, Line, Point Yes 
SDK Yes 
Supports Audio Files Yes 
Task Management Yes 
Team Collaboration Yes 
Training Data Management Yes 

Machine Learning

Deep Learning No 
ML Algorithm Library No 
Model Training No 
Natural Language Processing (NLP) No 
Predictive Modeling No 
Statistical / Mathematical Tools No 
Templates No 
Visualization No 

Product Features

Machine Learning

Deep Learning No 
ML Algorithm Library No 
Model Training No 
Natural Language Processing (NLP) No 
Predictive Modeling No 
Statistical / Mathematical Tools No 
Templates No 
Visualization No 

Version Control

Branch Creation / Deletion No 
Centralized Version History No 
Code Review No 
Code Version Management No 
Collaboration Tools No 
Compare / Merge Branches No 
Digital Asset / Binary File Storage No 
Isolated Code Branches No 
Option to Revert to Previous No 
Pull Requests No 
Roles / Permissions No 

Alternatives

Alternatives

TensorBoard Reviews

TensorBoard

Tensorflow