Azure Machine LearningMicrosoft
|
RayAnyscale
|
|||||
Related Products
|
||||||
About
Accelerate the end-to-end machine learning lifecycle. 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
Develop on your laptop and then scale the same Python code elastically across hundreds of nodes or GPUs on any cloud, with no changes. Ray translates existing Python concepts to the distributed setting, allowing any serial application to be easily parallelized with minimal code changes. Easily scale compute-heavy machine learning workloads like deep learning, model serving, and hyperparameter tuning with a strong ecosystem of distributed libraries. Scale existing workloads (for eg. Pytorch) on Ray with minimal effort by tapping into integrations. Native Ray libraries, such as Ray Tune and Ray Serve, lower the effort to scale the most compute-intensive machine learning workloads, such as hyperparameter tuning, training deep learning models, and reinforcement learning. For example, get started with distributed hyperparameter tuning in just 10 lines of code. Creating distributed apps is hard. Ray handles all aspects of distributed execution.
|
|||||
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
Data scientists, AI, and machine learning developers
|
Audience
ML and AI Engineers, Software Developers
|
|||||
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
Free
Free Version
Free Trial
|
|||||
Reviews/
|
Reviews/
|
|||||
Training
Documentation
Webinars
Live Online
In Person
|
Training
Documentation
Webinars
Live Online
In Person
|
|||||
Company InformationMicrosoft
Founded: 1975
United States
azure.microsoft.com/en-us/services/machine-learning/
|
Company InformationAnyscale
Founded: 2019
United States
ray.io
|
|||||
Alternatives |
Alternatives |
|||||
|
||||||
|
|
|||||
|
|
|||||
Categories |
Categories |
|||||
Machine Learning Features
Deep Learning
ML Algorithm Library
Model Training
Natural Language Processing (NLP)
Predictive Modeling
Statistical / Mathematical Tools
Templates
Visualization
Data Labeling Features
Human-in-the-loop
Labeling Automation
Labeling Quality
Performance Tracking
Polygon, Rectangle, Line, Point
SDK
Supports Audio Files
Task Management
Team Collaboration
Training Data Management
|
||||||
Integrations
MLflow
Amazon EC2 Trn2 Instances
Azure AI Search
Azure Container Registry
Azure Data Science Virtual Machines
Azure Database for MariaDB
Azure Kubernetes Service (AKS)
Azure Percept
Cranium
Dask
|
Integrations
MLflow
Amazon EC2 Trn2 Instances
Azure AI Search
Azure Container Registry
Azure Data Science Virtual Machines
Azure Database for MariaDB
Azure Kubernetes Service (AKS)
Azure Percept
Cranium
Dask
|
|||||
|
|