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Average Ratings 0 Ratings

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features
design
support

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Write a Review

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.

Description

Amazon SageMaker Studio Lab offers a complimentary environment for machine learning (ML) development, ensuring users have access to compute resources, storage of up to 15GB, and essential security features without any charge, allowing anyone to explore and learn about ML. To begin using this platform, all that is required is an email address; there is no need to set up infrastructure, manage access controls, or create an AWS account. It enhances the process of model development with seamless integration with GitHub and is equipped with widely-used ML tools, frameworks, and libraries for immediate engagement. Additionally, SageMaker Studio Lab automatically saves your progress, meaning you can easily pick up where you left off without needing to restart your sessions. You can simply close your laptop and return whenever you're ready to continue. This free development environment is designed specifically to facilitate learning and experimentation in machine learning. With its user-friendly setup, you can dive into ML projects right away, making it an ideal starting point for both newcomers and seasoned practitioners.

API Access

Has API No 

API Access

Has API No 

Screenshots View All

Screenshots View All

Integrations

Amazon SageMaker 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 Unified Studio Yes 
Apache Spark Yes 
Facebook Ads Yes 
Google Analytics Yes 
JSON Yes 
Jupyter Notebook No 
Meta Ads Yes 
PySpark Yes 
PyTorch No 
SAP Cloud Platform Yes 
Snowflake Yes 
TensorFlow No 
pandas Yes 

Integrations

Amazon SageMaker 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 Unified Studio No 
Apache Spark No 
Facebook Ads No 
Google Analytics No 
JSON No 
Jupyter Notebook Yes 
Meta Ads No 
PySpark No 
PyTorch Yes 
SAP Cloud Platform No 
Snowflake No 
TensorFlow Yes 
pandas No 

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) Yes 
Online Support Yes 

Customer Support

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

Types of Training

Training Docs Yes 
Webinars Yes 
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

1994

Country

United States

Website

aws.amazon.com/sagemaker/data-wrangler/

Vendor Details

Company Name

Amazon

Founded

1994

Country

United States

Website

aws.amazon.com/sagemaker/studio-lab/

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 

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 

Alternatives

Alternatives