+
+

Related Products

  • RunPod
    205 Ratings
    Visit Website
  • Vertex AI
    783 Ratings
    Visit Website
  • TrustInSoft Analyzer
    6 Ratings
    Visit Website
  • OORT DataHub
    13 Ratings
    Visit Website
  • Sage Intacct
    7,861 Ratings
    Visit Website
  • Fraud.net
    56 Ratings
    Visit Website
  • Google Cloud BigQuery
    1,934 Ratings
    Visit Website
  • ManageEngine Log360
    140 Ratings
    Visit Website
  • EBizCharge
    195 Ratings
    Visit Website
  • Blumira
    145 Ratings
    Visit Website

About

Optimize ML models by capturing training metrics in real-time and sending alerts when anomalies are detected. Automatically stop training processes when the desired accuracy is achieved to reduce the time and cost of training ML models. Automatically profile and monitor system resource utilization and send alerts when resource bottlenecks are identified to continuously improve resource utilization. Amazon SageMaker Debugger can reduce troubleshooting during training from days to minutes by automatically detecting and alerting you to remediate common training errors such as gradient values becoming too large or too small. Alerts can be viewed in Amazon SageMaker Studio or configured through Amazon CloudWatch. Additionally, the SageMaker Debugger SDK enables you to automatically detect new classes of model-specific errors such as data sampling, hyperparameter values, and out-of-bound values.

About

Don't change your day-to-day, works with Jupyter Notebooks and any other Python environment. Simply call modelbi.deploy to deploy your model, and let Modelbit carry it — and all its dependencies — to production. ML models deployed with Modelbit can be called directly from your warehouse as easily as calling a SQL function. They can also be called as a REST endpoint directly from your product. Modelbit is backed by your git repo. GitHub, GitLab, or home grown. Code review. CI/CD pipelines. PRs and merge requests. Bring your whole git workflow to your Python ML models. Modelbit integrates seamlessly with Hex, DeepNote, Noteable and more. Take your model straight from your favorite cloud notebook into production. Sick of VPC configurations and IAM roles? Seamlessly redeploy your SageMaker models to Modelbit. Immediately reap the benefits of Modelbit's platform with the models you've already built.

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

Businesses seeking a tool to optimize ML models with real-time monitoring of training metrics and system resources

Audience

Data scientists searching for a complete Machine Learning solution

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

No information available.
Free Version
Free Trial

Pricing

No information available.
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

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
Webinars
Live Online
In Person

Training

Documentation
Webinars
Live Online
In Person

Company Information

Amazon
Founded: 1994
United States
aws.amazon.com/sagemaker/debugger/

Company Information

Modelbit
Founded: 2022
United States
www.modelbit.com

Alternatives

Alternatives

Categories

Categories

Integrations

PyTorch
TensorFlow
AWS Lambda
Amazon CloudWatch
Amazon Redshift
Amazon SageMaker
Amazon SageMaker Studio
Amazon SageMaker Unified Studio
Amazon Web Services (AWS)
Change Healthcare Data & Analytics
Databricks Data Intelligence Platform
Deepnote
GitHub
GitLab
Google Colab
Jupyter Notebook
Keras
MXNet
Snowflake

Integrations

PyTorch
TensorFlow
AWS Lambda
Amazon CloudWatch
Amazon Redshift
Amazon SageMaker
Amazon SageMaker Studio
Amazon SageMaker Unified Studio
Amazon Web Services (AWS)
Change Healthcare Data & Analytics
Databricks Data Intelligence Platform
Deepnote
GitHub
GitLab
Google Colab
Jupyter Notebook
Keras
MXNet
Snowflake
Claim Amazon SageMaker Debugger and update features and information
Claim Amazon SageMaker Debugger and update features and information
Claim Modelbit and update features and information
Claim Modelbit and update features and information