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What is Amazon SageMaker?

Amazon SageMaker is a robust platform designed to help developers efficiently build, train, and deploy machine learning models. It unites a wide range of tools in a single, integrated environment that accelerates the creation and deployment of both traditional machine learning models and generative AI applications. SageMaker enables seamless data access from diverse sources like Amazon S3 data lakes, Redshift data warehouses, and third-party databases, while offering secure, real-time data processing. The platform provides specialized features for AI use cases, including generative AI, and tools for model training, fine-tuning, and deployment at scale. It also supports enterprise-level security with fine-grained access controls, ensuring compliance and transparency throughout the AI lifecycle. By offering a unified studio for collaboration, SageMaker improves teamwork and productivity. Its comprehensive approach to governance, data management, and model monitoring gives users full confidence in their AI projects.

What is 3LC?

Illuminate the opaque processes of your models by integrating 3LC, enabling the essential insights required for swift and impactful changes. By removing uncertainty from the training phase, you can expedite the iteration process significantly. Capture metrics for each individual sample and display them conveniently in your web interface for easy analysis. Scrutinize your training workflow to detect and rectify issues within your dataset effectively. Engage in interactive debugging guided by your model, facilitating data enhancement in a streamlined manner. Uncover both significant and ineffective samples, allowing you to recognize which features yield positive results and where the model struggles. Improve your model using a variety of approaches by fine-tuning the weight of your data accordingly. Implement precise modifications, whether to single samples or in bulk, while maintaining a detailed log of all adjustments, enabling effortless reversion to any previous version. Go beyond standard experiment tracking by organizing metrics based on individual sample characteristics instead of solely by epoch, revealing intricate patterns that may otherwise go unnoticed. Ensure that each training session is meticulously associated with a specific dataset version, which guarantees complete reproducibility throughout the process. With these advanced tools at your fingertips, the journey of refining your models transforms into a more insightful and finely tuned endeavor, ultimately leading to better performance and understanding of your systems. Additionally, this approach empowers you to foster a more data-driven culture within your team, promoting collaborative exploration and innovation.

Media

Media

Integrations Supported

Amazon Web Services (AWS)
AWS Clean Rooms
AWS IAM Identity Center
AWS Neuron
Akira AI
Amazon EC2 G4 Instances
Amazon EC2 Inf1 Instances
Amazon EC2 P5 Instances
Amazon SageMaker Debugger
BentoML
Cameralyze
Coral
Darktrace / SECURE AI
DataHub
Datasaur
Deepchecks
Label Studio
New Relic

Integrations Supported

Amazon Web Services (AWS)
Microsoft Azure
NumPy

API Availability

Has API

API Availability

Pricing Information

Try free for two months
Free Trial Offered?

Pricing Information

Pricing not provided

Supported Platforms

SaaS

Supported Platforms

Windows
Mac
Linux

Customer Service / Support

Web-Based Support

Customer Service / Support

Web-Based Support

Training Options

Online Training

Training Options

Documentation Hub

Company Facts

Organization Name

Amazon

Date Founded

1994

Company Location

United States

Company Website

aws.amazon.com/sagemaker/

Company Facts

Organization Name

3LC

Company Website

3lc.ai/

Categories and Features

Agentic AI

Not specified

AI Development

Not specified

AI Fine-Tuning

Not specified

AI Governance

Not specified

AI Infrastructure

Not specified

AI Tools

Not specified

AI/ML Model Training

Not specified

Data Catalog

Not specified

Data Governance

Not specified

Data Labeling

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

Machine Learning

Not specified

ML Model Deployment

Not specified

ML Model Management

Not specified

Categories and Features

AI/ML Model Training

Not specified

Machine Learning

Not specified

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