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ease
features
design
support

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Description

Amazon SageMaker Canvas democratizes access to machine learning by equipping business analysts with an intuitive visual interface that enables them to independently create precise ML predictions without needing prior ML knowledge or coding skills. This user-friendly point-and-click interface facilitates the connection, preparation, analysis, and exploration of data, simplifying the process of constructing ML models and producing reliable predictions. Users can effortlessly build ML models to conduct what-if scenarios and generate both individual and bulk predictions with minimal effort. The platform enhances teamwork between business analysts and data scientists, allowing for the seamless sharing, reviewing, and updating of ML models across different tools. Additionally, users can import ML models from various sources and obtain predictions directly within Amazon SageMaker Canvas. With this tool, you can draw data from diverse origins, specify the outcomes you wish to forecast, and automatically prepare as well as examine your data, enabling a swift and straightforward model-building experience. Ultimately, this capability allows users to analyze their models and yield accurate predictions, fostering a more data-driven decision-making culture across organizations.

Description

Utilize open-source machine learning tools and data visualization techniques to create dynamic data analysis workflows in a visual format, supported by a broad and varied collection of resources. Conduct straightforward data assessments accompanied by insightful visual representations, and investigate statistical distributions through box plots and scatter plots; for more complex inquiries, utilize decision trees, hierarchical clustering, heatmaps, multidimensional scaling, and linear projections. Even intricate multidimensional datasets can be effectively represented in 2D, particularly through smart attribute selection and ranking methods. Engage in interactive data exploration for swift qualitative analysis, enhanced by clear visual displays. The user-friendly graphic interface enables a focus on exploratory data analysis rather than programming, while intelligent defaults facilitate quick prototyping of data workflows. Simply position widgets on your canvas, link them together, import your datasets, and extract valuable insights! When it comes to teaching data mining concepts, we prefer to demonstrate rather than merely describe, and Orange excels in making this approach effective and engaging. The platform not only simplifies the process but also enriches the learning experience for users at all levels.

API Access

Has API

API Access

Has API

Screenshots View All

Screenshots View All

Integrations

Amazon SageMaker
Amazon SageMaker Unified Studio
Amazon Web Services (AWS)

Integrations

Amazon SageMaker
Amazon SageMaker Unified Studio
Amazon Web Services (AWS)

Pricing Details

No price information available.
Free Trial
Free Version

Pricing Details

No price information available.
Free Trial
Free Version

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Vendor Details

Company Name

Amazon

Founded

1994

Country

United States

Website

aws.amazon.com/sagemaker/canvas/

Vendor Details

Company Name

University of Ljubljana

Country

Slovenia

Website

orange.biolab.si

Product Features

Machine Learning

Deep Learning
ML Algorithm Library
Model Training
Natural Language Processing (NLP)
Predictive Modeling
Statistical / Mathematical Tools
Templates
Visualization

Product Features

Data Mining

Data Extraction
Data Visualization
Fraud Detection
Linked Data Management
Machine Learning
Predictive Modeling
Semantic Search
Statistical Analysis
Text Mining

Data Visualization

Analytics
Content Management
Dashboard Creation
Filtered Views
OLAP
Relational Display
Simulation Models
Visual Discovery

Machine Learning

Deep Learning
ML Algorithm Library
Model Training
Natural Language Processing (NLP)
Predictive Modeling
Statistical / Mathematical Tools
Templates
Visualization

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