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

The core of extensible programming is defining functions. Python allows mandatory and optional arguments, keyword arguments, and even arbitrary argument lists. Whether you're new to programming or an experienced developer, it's easy to learn and use Python. Python can be easy to pick up whether you're a first-time programmer or you're experienced with other languages. The following pages are a useful first step to get on your way to writing programs with Python! The community hosts conferences and meetups to collaborate on code, and much more. Python's documentation will help you along the way, and the mailing lists will keep you in touch. The Python Package Index (PyPI) hosts thousands of third-party modules for Python. Both Python's standard library and the community-contributed modules allow for endless possibilities.

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

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 interested in a beautiful but advanced programming language

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

Support

Phone Support
24/7 Live Support
Online

API

Offers API

API

Offers API

API

Offers API

Screenshots and Videos

Screenshots and Videos

Screenshots and Videos

Pricing

No information available.
Free Version
Free Trial

Pricing

Free
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 5.0 / 5
ease 5.0 / 5
features 5.0 / 5
design 5.0 / 5
support 5.0 / 5

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

Training

Documentation
Webinars
Live Online
In Person

Company Information

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

Company Information

Python
Founded: 1991
www.python.org

Company Information

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

Alternatives

Apache Spark

Apache Spark

Apache Software Foundation

Alternatives

Alternatives

Gensim

Gensim

Radim Řehůřek
ML.NET

ML.NET

Microsoft
Apache Mahout

Apache Mahout

Apache Software Foundation
MLlib

MLlib

Apache Software Foundation
Amazon EMR

Amazon EMR

Amazon
Keepsake

Keepsake

Replicate

Categories

Categories

Categories

Integrations

AWS Thinkbox Deadline
Actian Ingres
AgentKit
Amazon Q Business
CZ CELLxGENE Discover
Cloud 66
CudaText
Firecrawl
Hyland Document Filters
Komodo Edit
Kontra
Modelscape
Ndustrial Contxt
Peliqan
Postcoder
Queue-it
ScrapeOwl
Service Objects Email Validation
Taipy
Zama

Integrations

AWS Thinkbox Deadline
Actian Ingres
AgentKit
Amazon Q Business
CZ CELLxGENE Discover
Cloud 66
CudaText
Firecrawl
Hyland Document Filters
Komodo Edit
Kontra
Modelscape
Ndustrial Contxt
Peliqan
Postcoder
Queue-it
ScrapeOwl
Service Objects Email Validation
Taipy
Zama

Integrations

AWS Thinkbox Deadline
Actian Ingres
AgentKit
Amazon Q Business
CZ CELLxGENE Discover
Cloud 66
CudaText
Firecrawl
Hyland Document Filters
Komodo Edit
Kontra
Modelscape
Ndustrial Contxt
Peliqan
Postcoder
Queue-it
ScrapeOwl
Service Objects Email Validation
Taipy
Zama
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