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

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
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

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

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/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

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

Alternatives

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Apache Mahout

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Alternatives

Gensim

Gensim

Radim Řehůřek
Apache Spark

Apache Spark

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ML.NET

ML.NET

Microsoft
MLlib

MLlib

Apache Software Foundation
ML.NET

ML.NET

Microsoft
Keepsake

Keepsake

Replicate

Categories

Categories

Integrations

Python
Amazon EC2
Apache Cassandra
Apache HBase
Apache Hive
Apache Spark
DagsHub
Flower
Guild AI
Hadoop
Intel Tiber AI Studio
Java
Kubernetes
MLJAR Studio
MapReduce
Matplotlib
ModelOp
NumPy
R
Scala

Integrations

Python
Amazon EC2
Apache Cassandra
Apache HBase
Apache Hive
Apache Spark
DagsHub
Flower
Guild AI
Hadoop
Intel Tiber AI Studio
Java
Kubernetes
MLJAR Studio
MapReduce
Matplotlib
ModelOp
NumPy
R
Scala
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