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Average Ratings 0 Ratings

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ease
features
design
support

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Write a Review

Description

An all-inclusive platform that offers a wide array of machine learning algorithms tailored to fulfill your data mining and analytical needs. The Machine Learning Platform for AI delivers comprehensive machine learning solutions, encompassing data preprocessing, feature selection, model development, predictions, and performance assessment. This platform integrates these various services to enhance the accessibility of artificial intelligence like never before. With a user-friendly web interface, the Machine Learning Platform for AI allows users to design experiments effortlessly by simply dragging and dropping components onto a canvas. The process of building machine learning models is streamlined into a straightforward, step-by-step format, significantly boosting efficiency and lowering costs during experiment creation. Featuring over one hundred algorithm components, the Machine Learning Platform for AI addresses diverse scenarios, including regression, classification, clustering, text analysis, finance, and time series forecasting, catering to a wide range of analytical tasks. This comprehensive approach ensures that users can tackle any data challenge with confidence and ease.

Description

MLlib, the machine learning library of Apache Spark, is designed to be highly scalable and integrates effortlessly with Spark's various APIs, accommodating programming languages such as Java, Scala, Python, and R. It provides an extensive range of algorithms and utilities, which encompass classification, regression, clustering, collaborative filtering, and the capabilities to build machine learning pipelines. By harnessing Spark's iterative computation features, MLlib achieves performance improvements that can be as much as 100 times faster than conventional MapReduce methods. Furthermore, it is built to function in a variety of environments, whether on Hadoop, Apache Mesos, Kubernetes, standalone clusters, or within cloud infrastructures, while also being able to access multiple data sources, including HDFS, HBase, and local files. This versatility not only enhances its usability but also establishes MLlib as a powerful tool for executing scalable and efficient machine learning operations in the Apache Spark framework. The combination of speed, flexibility, and a rich set of features renders MLlib an essential resource for data scientists and engineers alike.

API Access

Has API Yes 

API Access

Has API Yes 

Screenshots View All

Screenshots View All

Integrations

Alibaba Cloud Yes 
Amazon EC2 No 
Apache Cassandra No 
Apache HBase No 
Apache Hive No 
Apache Mesos No 
Apache Spark No 
Hadoop No 
Java No 
Kubernetes No 
MapReduce No 
Python No 
R No 
Scala No 
ZSvirt Yes 

Integrations

Alibaba Cloud No 
Amazon EC2 Yes 
Apache Cassandra Yes 
Apache HBase Yes 
Apache Hive Yes 
Apache Mesos Yes 
Apache Spark Yes 
Hadoop Yes 
Java Yes 
Kubernetes Yes 
MapReduce Yes 
Python Yes 
R Yes 
Scala Yes 
ZSvirt No 

Pricing Details

$1.872 per hour
Free Trial Yes 
Free Version No 

Pricing Details

No price information available.
Free Trial No 
Free Version No 

Deployment

Web-Based Yes 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
Linux No 
Chromebook No 

Deployment

Web-Based Yes 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
Linux No 
Chromebook No 

Customer Support

Business Hours Yes 
Live Rep (24/7) Yes 
Online Support Yes 

Customer Support

Business Hours Yes 
Live Rep (24/7) No 
Online Support Yes 

Types of Training

Training Docs Yes 
Webinars Yes 
Live Training (Online) No 
In Person No 

Types of Training

Training Docs Yes 
Webinars Yes 
Live Training (Online) No 
In Person Yes 

Vendor Details

Company Name

Alibaba Cloud

Founded

2008

Country

China

Website

www.alibabacloud.com/product/machine-learning

Vendor Details

Company Name

Apache Software Foundation

Founded

1995

Country

United States

Website

spark.apache.org/mllib/

Product Features

Machine Learning

Deep Learning No 
ML Algorithm Library No 
Model Training No 
Natural Language Processing (NLP) No 
Predictive Modeling No 
Statistical / Mathematical Tools No 
Templates No 
Visualization No 

Product Features

Machine Learning

Deep Learning No 
ML Algorithm Library No 
Model Training No 
Natural Language Processing (NLP) No 
Predictive Modeling No 
Statistical / Mathematical Tools No 
Templates No 
Visualization No 

Alternatives

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