MLlib

MLlib

Apache Software Foundation
MXNet

MXNet

The 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

A hybrid front-end seamlessly transitions between Gluon eager imperative mode and symbolic mode to provide both flexibility and speed. Scalable distributed training and performance optimization in research and production is enabled by the dual parameter server and Horovod support. Deep integration into Python and support for Scala, Julia, Clojure, Java, C++, R and Perl. A thriving ecosystem of tools and libraries extends MXNet and enables use-cases in computer vision, NLP, time series and more. Apache MXNet is an effort undergoing incubation at The Apache Software Foundation (ASF), sponsored by the Apache Incubator. Incubation is required of all newly accepted projects until a further review indicates that the infrastructure, communications, and decision-making process have stabilized in a manner consistent with other successful ASF projects. Join the MXNet scientific community to contribute, learn, and get answers to your questions.

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

Developers and researchers requiring an open-source deep learning framework for research prototyping and production

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

The Apache Software Foundation
Founded: 1999
United States
mxnet.apache.org

Alternatives

Apache Spark

Apache Spark

Apache Software Foundation

Alternatives

Apache Mahout

Apache Mahout

Apache Software Foundation
Amazon EMR

Amazon EMR

Amazon
Caffe

Caffe

BAIR

Categories

Categories

Integrations

AWS Marketplace
Amazon EC2 Inf1 Instances
Amazon EC2 P4 Instances
Amazon SageMaker Debugger
Apache Cassandra
Apache HBase
Apache Hive
Apache Mesos
Google Cloud Deep Learning VM Image
Gradient
Guild AI
Hadoop
Horovod
LeaderGPU
MLReef
MapReduce
NVIDIA Triton Inference Server
Python
Scala

Integrations

AWS Marketplace
Amazon EC2 Inf1 Instances
Amazon EC2 P4 Instances
Amazon SageMaker Debugger
Apache Cassandra
Apache HBase
Apache Hive
Apache Mesos
Google Cloud Deep Learning VM Image
Gradient
Guild AI
Hadoop
Horovod
LeaderGPU
MLReef
MapReduce
NVIDIA Triton Inference Server
Python
Scala
Claim MLlib and update features and information
Claim MLlib and update features and information
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