Create MLApple
|
FlyteUnion.ai
|
|||||
Related Products
|
||||||
About
Experience an entirely new way of training machine learning models on your Mac. Create ML takes the complexity out of model training while producing powerful Core ML models. Train multiple models using different datasets, all in a single project. Preview your model performance using Continuity with your iPhone camera and microphone on your Mac, or drop in sample data. Pause, save, resume, and extend your training process. Interactively learn how your model performs on test data from your evaluation set. Explore key metrics and their connections to specific examples to help identify challenging use cases, further investments in data collection, and opportunities to help improve model quality. Use an external graphics processing unit with your Mac for even better model training performance. Train models blazingly fast right on your Mac while taking advantage of CPU and GPU. Create ML has a variety of model types to choose from.
|
About
The workflow automation platform for complex, mission-critical data and ML processes at scale. Flyte makes it easy to create concurrent, scalable, and maintainable workflows for machine learning and data processing. Flyte is used in production at Lyft, Spotify, Freenome, and others. At Lyft, Flyte has been serving production model training and data processing for over four years, becoming the de-facto platform for teams like pricing, locations, ETA, mapping, autonomous, and more. In fact, Flyte manages over 10,000 unique workflows at Lyft, totaling over 1,000,000 executions every month, 20 million tasks, and 40 million containers. Flyte has been battle-tested at Lyft, Spotify, Freenome, and others. It is entirely open-source with an Apache 2.0 license under the Linux Foundation with a cross-industry overseeing committee. Configuring machine learning and data workflows can get complex and error-prone with YAML.
|
|||||
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
Not 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
Professional users seeking a tool to train multiple machine learning models using different datasets
|
Audience
Developers in need of a workflow automation platform to create concurrent, scalable, and maintainable workflows
|
|||||
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
Not Supported
|
Pricing
Free
Free Version
Supported
Free Trial
Not Supported
|
|||||
Reviews/
|
Reviews/
|
|||||
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 InformationApple
United States
developer.apple.com/machine-learning/create-ml/
|
Company InformationUnion.ai
Founded: 2020
United States
flyte.org
|
|||||
Alternatives |
Alternatives |
|||||
|
|
||||||
|
|
||||||
|
|
||||||
|
|
||||||
Categories |
Categories |
|||||
Integrations
Amazon SageMaker
Not Supported
Apache Parquet
Not Supported
Apache Spark
Not Supported
Dask
Not Supported
Databricks
Not Supported
DuckDB
Not Supported
Google Cloud Platform
Not Supported
Horovod
Not Supported
Hugging Face
Not Supported
MLflow
Not Supported
|
Integrations
Amazon SageMaker
Supported
Apache Parquet
Supported
Apache Spark
Supported
Dask
Supported
Databricks
Supported
DuckDB
Supported
Google Cloud Platform
Supported
Horovod
Supported
Hugging Face
Supported
MLflow
Supported
|
|||||
|
|
|