evoML

evoML

TurinTech AI
+
+

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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

evoML accelerates the creation of production-quality machine learning models by streamlining and automating the end-to-end data science workflow, transforming raw data into actionable insights in days instead of weeks. It automates crucial steps, automatic data transformation that detects anomalies and handles imbalances, feature engineering via genetic algorithms, parallel model evaluation across thousands of candidates, multi-objective optimization on custom metrics, and GenAI-based synthetic data generation for rapid prototyping under data-privacy constraints. Users fully own and customize generated model code for seamless deployment as APIs, databases, or local libraries, avoiding vendor lock-in and ensuring transparent, auditable workflows. EvoML empowers teams with intuitive visualizations, interactive dashboards, and charts to identify patterns, outliers, and anomalies for use cases such as anomaly detection, time-series forecasting, and fraud prevention.

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, ML engineers and business analysts requiring a solution to build, optimize and deploy production-grade machine learning models from their existing data with minimal manual effort

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

TurinTech AI
Founded: 2018
United Kingdom
www.turintech.ai/evoml

Alternatives

Alternatives

Categories

Categories

Integrations

AWS Lambda
Amazon CloudWatch
Amazon SageMaker
Amazon SageMaker Studio
Amazon SageMaker Unified Studio
Amazon Web Services (AWS)
Change Healthcare Data & Analytics
Keras
MXNet
PyTorch
TensorFlow

Integrations

AWS Lambda
Amazon CloudWatch
Amazon SageMaker
Amazon SageMaker Studio
Amazon SageMaker Unified Studio
Amazon Web Services (AWS)
Change Healthcare Data & Analytics
Keras
MXNet
PyTorch
TensorFlow
Claim Amazon SageMaker Debugger and update features and information
Claim Amazon SageMaker Debugger and update features and information
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Claim evoML and update features and information