Average Ratings 0 Ratings
Average Ratings 0 Ratings
Description
Amazon SageMaker Autopilot streamlines the process of creating machine learning models by handling the complex tasks involved. All you need to do is upload a tabular dataset and choose the target column for prediction, and then SageMaker Autopilot will systematically evaluate various strategies to identify the optimal model. From there, you can easily deploy the model into a production environment with a single click or refine the suggested solutions to enhance the model’s performance further. Additionally, SageMaker Autopilot is capable of working with datasets that contain missing values, as it automatically addresses these gaps, offers statistical insights on the dataset's columns, and retrieves relevant information from non-numeric data types, including extracting date and time details from timestamps. This functionality makes it a versatile tool for users looking to leverage machine learning without deep technical expertise.
Description
Amazon SageMaker Data Wrangler significantly shortens the data aggregation and preparation timeline for machine learning tasks from several weeks to just minutes. This tool streamlines data preparation and feature engineering, allowing you to execute every phase of the data preparation process—such as data selection, cleansing, exploration, visualization, and large-scale processing—through a unified visual interface. You can effortlessly select data from diverse sources using SQL, enabling rapid imports. Following this, the Data Quality and Insights report serves to automatically assess data integrity and identify issues like duplicate entries and target leakage. With over 300 pre-built data transformations available, SageMaker Data Wrangler allows for quick data modification without the need for coding. After finalizing your data preparation, you can scale the workflow to encompass your complete datasets, facilitating model training, tuning, and deployment in a seamless manner. This comprehensive approach not only enhances efficiency but also empowers users to focus on deriving insights from their data rather than getting bogged down in the preparation phase.
API Access
Has API
No
API Access
Has API
No
Integrations
Amazon SageMaker
Yes
Amazon SageMaker Unified Studio
Yes
Amazon Web Services (AWS)
Yes
Amazon Athena
No
Amazon EMR
No
Amazon Redshift
No
Amazon S3
No
Amazon SageMaker Feature Store
No
Amazon SageMaker Studio
No
Apache Parquet
No
Integrations
Amazon SageMaker
Yes
Amazon SageMaker Unified Studio
Yes
Amazon Web Services (AWS)
Yes
Amazon Athena
Yes
Amazon EMR
Yes
Amazon Redshift
Yes
Amazon S3
Yes
Amazon SageMaker Feature Store
Yes
Amazon SageMaker Studio
Yes
Apache Parquet
Yes
Pricing Details
No price information available.
Free Trial
No
Free Version
No
Pricing Details
No price information available.
Free Trial
No
Free Version
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
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)
Yes
Online Support
Yes
Types of Training
Training Docs
Yes
Webinars
No
Live Training (Online)
No
In Person
No
Types of Training
Training Docs
Yes
Webinars
Yes
Live Training (Online)
No
In Person
No
Vendor Details
Company Name
Amazon
Founded
2006
Country
United States
Website
aws.amazon.com/sagemaker/autopilot
Vendor Details
Company Name
Amazon
Founded
1994
Country
United States
Website
aws.amazon.com/sagemaker/data-wrangler/
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
Product Features
Data Preparation
Collaboration Tools
No
Data Access
No
Data Blending
No
Data Cleansing
No
Data Governance
No
Data Mashup
No
Data Modeling
No
Data Transformation
No
Machine Learning
No
Visual User Interface
No
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