MLlibApache Software Foundation
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WekaUniversity of Waikato
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Related Products
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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.
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About
Weka is a collection of machine learning algorithms for data mining tasks. It contains tools for data preparation, classification, regression, clustering, association rules mining, and visualization. Found only on the islands of New Zealand, the Weka is a flightless bird with an inquisitive nature. The name is pronounced like this, and the bird sounds like this. Weka is open source software issued under the GNU General Public License. We have put together several free online courses that teach machine learning and data mining using Weka. The videos for the courses are available on Youtube. An exciting and potentially far-reaching development in computer science is the invention and application of methods of machine learning (ML). These enable a computer program to automatically analyze a large body of data and decide what information is most relevant. This crystallized information can then be used to automatically make predictions or to help people make decisions faster.
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Platforms Supported
Windows
Not Supported
Mac
Not Supported
Linux
Not Supported
Cloud
Supported
On-Premises
Not Supported
iPhone
Not Supported
iPad
Not Supported
Android
Not Supported
Chromebook
Not Supported
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Platforms Supported
Windows
Not Supported
Mac
Not Supported
Linux
Not Supported
Cloud
Supported
On-Premises
Not Supported
iPhone
Not Supported
iPad
Not Supported
Android
Not Supported
Chromebook
Not Supported
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Audience
Data scientists and engineers wanting a machine learning solution for efficient data processing and analysis within the Apache Spark framework
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Audience
Companies, researchers and organizations in need of a machine learning solution for their projects
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Support
Phone Support
Supported
24/7 Live Support
Not Supported
Online
Supported
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Support
Phone Support
Not Supported
24/7 Live Support
Not Supported
Online
Supported
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API
Offers API
Supported
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API
Offers API
Not Supported
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Screenshots and Videos |
Screenshots and Videos |
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Pricing
No information available.
Free Version
Not Supported
Free Trial
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Pricing
No information available.
Free Version
Not Supported
Free Trial
Not Supported
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Reviews/
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Reviews/
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Training
Documentation
Supported
Webinars
Supported
Live Online
Not Supported
In Person
Supported
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Training
Documentation
Supported
Webinars
Not Supported
Live Online
Not Supported
In Person
Not Supported
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Company InformationApache Software Foundation
Founded: 1995
United States
spark.apache.org/mllib/
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Company InformationUniversity of Waikato
New Zealand
www.cs.waikato.ac.nz/ml/weka/
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Categories |
Categories |
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Machine Learning Features
Deep Learning
Not Supported
ML Algorithm Library
Supported
Model Training
Not Supported
Natural Language Processing (NLP)
Not Supported
Predictive Modeling
Supported
Statistical / Mathematical Tools
Not Supported
Templates
Not Supported
Visualization
Supported
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Integrations
AWS Marketplace
Not Supported
Amazon EC2
Supported
Apache Cassandra
Supported
Apache HBase
Supported
Apache Hive
Supported
Apache Mesos
Supported
Apache Spark
Supported
Hadoop
Supported
Java
Supported
Kubernetes
Supported
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Integrations
AWS Marketplace
Supported
Amazon EC2
Not Supported
Apache Cassandra
Not Supported
Apache HBase
Not Supported
Apache Hive
Not Supported
Apache Mesos
Not Supported
Apache Spark
Not Supported
Hadoop
Not Supported
Java
Not Supported
Kubernetes
Not Supported
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