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About

Accelerate the end-to-end machine learning lifecycle with Azure Machine Learning Studio. Empower developers and data scientists with a wide range of productive experiences for building, training, and deploying machine learning models faster. Accelerate time to market and foster team collaboration with industry-leading MLOps—DevOps for machine learning. Innovate on a secure, trusted platform, designed for responsible ML. Productivity for all skill levels, with code-first and drag-and-drop designer, and automated machine learning. Robust MLOps capabilities that integrate with existing DevOps processes and help manage the complete ML lifecycle. Responsible ML capabilities – understand models with interpretability and fairness, protect data with differential privacy and confidential computing, and control the ML lifecycle with audit trials and datasheets. Best-in-class support for open-source frameworks and languages including MLflow, Kubeflow, ONNX, PyTorch, TensorFlow, Python, and R.

About

Scikit-learn provides simple and efficient tools for predictive data analysis. Scikit-learn is a robust, open source machine learning library for the Python programming language, designed to provide simple and efficient tools for data analysis and modeling. Built on the foundations of popular scientific libraries like NumPy, SciPy, and Matplotlib, scikit-learn offers a wide range of supervised and unsupervised learning algorithms, making it an essential toolkit for data scientists, machine learning engineers, and researchers. The library is organized into a consistent and flexible framework, where various components can be combined and customized to suit specific needs. This modularity makes it easy for users to build complex pipelines, automate repetitive tasks, and integrate scikit-learn into larger machine-learning workflows. Additionally, the library’s emphasis on interoperability ensures that it works seamlessly with other Python libraries, facilitating smooth data processing.

Platforms Supported

Windows Not Supported
Mac Not Supported
Linux Not Supported
Cloud Supported
On-Premises Not Supported
iPhone Not Supported
iPad Not Supported
Android Not Supported
Chromebook Not Supported

Platforms Supported

Windows Supported
Mac Supported
Linux Supported
Cloud Not Supported
On-Premises Not Supported
iPhone Not Supported
iPad Not Supported
Android Not Supported
Chromebook Not Supported

Audience

Data scientists, AI, and machine learning developers

Audience

Engineers and data scientists requiring a solution to manage and improve their machine learning research

Support

Phone Support Not Supported
24/7 Live Support Not Supported
Online Supported

Support

Phone Support Not Supported
24/7 Live Support Not Supported
Online Supported

API

Offers API Not Supported

API

Offers API Supported

Screenshots and Videos

Screenshots and Videos

Pricing

No information available.
Free Version Not Supported
Free Trial Supported

Pricing

Free
Free Version Supported
Free Trial Not Supported

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 Supported
Webinars Not Supported
Live Online Not Supported
In Person Not Supported

Training

Documentation Supported
Webinars Not Supported
Live Online Not Supported
In Person Not Supported

Company Information

Microsoft
Founded: 1975
United States
azure.microsoft.com/en-us/products/machine-learning/

Company Information

scikit-learn
United States
scikit-learn.org/stable/

Alternatives

Alternatives

Gensim

Gensim

Radim Řehůřek
ML.NET

ML.NET

Microsoft
MLlib

MLlib

Apache Software Foundation
Keepsake

Keepsake

Replicate

Categories

AI Development Supported
AI Governance Supported
AI Infrastructure Supported
Data Labeling Supported
Machine Learning Supported

Categories

Machine Learning Supported

Machine Learning Features

Deep Learning Not Supported
ML Algorithm Library Not Supported
Model Training Not Supported
Natural Language Processing (NLP) Not Supported
Predictive Modeling Supported
Statistical / Mathematical Tools Not Supported
Templates Not Supported
Visualization Not Supported

Data Labeling Features

Human-in-the-loop Supported
Labeling Automation Supported
Labeling Quality Supported
Performance Tracking Supported
Polygon, Rectangle, Line, Point Supported
SDK Supported
Supports Audio Files Supported
Task Management Supported
Team Collaboration Supported
Training Data Management Supported

Integrations

ModelOp Supported
Azure Container Registry Supported
Azure Data Science Virtual Machines Supported
Azure Database for MariaDB Supported
Cranium Supported
Databricks Not Supported
GLM-5.1 Not Supported
GLM-5.2 Not Supported
Kedro Supported
Keepsake Not Supported
MLflow Supported
Microsoft Intelligent Data Platform Supported
NVIDIA Triton Inference Server Supported
New Relic Supported
Python Not Supported
Slingshot Supported
Superwise Supported
Train in Data Not Supported
Visual Studio Code Supported
Wizata Supported

Integrations

ModelOp Supported
Azure Container Registry Not Supported
Azure Data Science Virtual Machines Not Supported
Azure Database for MariaDB Not Supported
Cranium Not Supported
Databricks Supported
GLM-5.1 Supported
GLM-5.2 Supported
Kedro Not Supported
Keepsake Supported
MLflow Not Supported
Microsoft Intelligent Data Platform Not Supported
NVIDIA Triton Inference Server Not Supported
New Relic Not Supported
Python Supported
Slingshot Not Supported
Superwise Not Supported
Train in Data Supported
Visual Studio Code Not Supported
Wizata Not Supported
Claim Azure Machine Learning and update features and information
Claim Azure Machine Learning and update features and information
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Claim scikit-learn and update features and information