MLlib

MLlib

Apache Software Foundation
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About

​Apache Spark's MLlib is a scalable machine learning library that integrates seamlessly with Spark's APIs, supporting Java, Scala, Python, and R. It offers a comprehensive suite of algorithms and utilities, including classification, regression, clustering, collaborative filtering, and tools for constructing machine learning pipelines. MLlib's high-quality algorithms leverage Spark's iterative computation capabilities, delivering performance up to 100 times faster than traditional MapReduce implementations. It is designed to operate across diverse environments, running on Hadoop, Apache Mesos, Kubernetes, standalone clusters, or in the cloud, and accessing various data sources such as HDFS, HBase, and local files. This flexibility makes MLlib a robust solution for scalable and efficient machine learning tasks within the Apache Spark ecosystem. ​

About

Transition seamlessly between eager and graph modes with TorchScript, and accelerate the path to production with TorchServe. Scalable distributed training and performance optimization in research and production is enabled by the torch-distributed backend. A rich ecosystem of tools and libraries extends PyTorch and supports development in computer vision, NLP and more. PyTorch is well supported on major cloud platforms, providing frictionless development and easy scaling. Select your preferences and run the install command. Stable represents the most currently tested and supported version of PyTorch. This should be suitable for many users. Preview is available if you want the latest, not fully tested and supported, 1.10 builds that are generated nightly. Please ensure that you have met the prerequisites (e.g., numpy), depending on your package manager. Anaconda is our recommended package manager since it installs all dependencies.

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 and engineers wanting a machine learning solution for efficient data processing and analysis within the Apache Spark framework

Audience

Researchers in need of an open source machine learning solution to accelerate research prototyping and production deployment

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

No information available.
Free Version
Free Trial

Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

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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
Webinars
Live Online
In Person

Training

Documentation
Webinars
Live Online
In Person

Company Information

Apache Software Foundation
Founded: 1995
United States
spark.apache.org/mllib/

Company Information

PyTorch
Founded: 2016
pytorch.org

Alternatives

Apache Spark

Apache Spark

Apache Software Foundation

Alternatives

Core ML

Core ML

Apple
Apache Mahout

Apache Mahout

Apache Software Foundation
Create ML

Create ML

Apple
Amazon EMR

Amazon EMR

Amazon
DeepSpeed

DeepSpeed

Microsoft
AWS Neuron

AWS Neuron

Amazon Web Services

Categories

Categories

Integrations

Amazon SageMaker Model Training
Apache HBase
Deeplake
Google Cloud Deep Learning VM Image
Google Cloud Platform
IBM Distributed AI APIs
Java
Keepsake
LiteRT
MLReef
Modelbit
NVIDIA Triton Inference Server
TensorWave
TorchMetrics
TrueFoundry
Voxel51
Voyager SDK
Yandex DataSphere

Integrations

Amazon SageMaker Model Training
Apache HBase
Deeplake
Google Cloud Deep Learning VM Image
Google Cloud Platform
IBM Distributed AI APIs
Java
Keepsake
LiteRT
MLReef
Modelbit
NVIDIA Triton Inference Server
TensorWave
TorchMetrics
TrueFoundry
Voxel51
Voyager SDK
Yandex DataSphere
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