MLlibApache Software Foundation
|
||||||
Related Products
|
||||||
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/
|
Reviews/
|
|||||
Training
Documentation
Webinars
Live Online
In Person
|
Training
Documentation
Webinars
Live Online
In Person
|
|||||
Company InformationApache Software Foundation
Founded: 1995
United States
spark.apache.org/mllib/
|
Company Informationscikit-learn
United States
scikit-learn.org/stable/
|
|||||
Alternatives |
Alternatives |
|||||
|
|
|||||
|
|
|||||
|
|
|||||
|
||||||
Categories |
Categories |
|||||
Integrations
Python
Amazon EC2
Apache Cassandra
Apache HBase
Apache Hive
Apache Spark
DagsHub
Flower
Guild AI
Hadoop
|
Integrations
Python
Amazon EC2
Apache Cassandra
Apache HBase
Apache Hive
Apache Spark
DagsHub
Flower
Guild AI
Hadoop
|
|||||
|
|