Ratings and Reviews 0 Ratings

Total
ease
features
design
support

This software has no reviews. Be the first to write a review.

Write a Review

Ratings and Reviews 0 Ratings

Total
ease
features
design
support

This software has no reviews. Be the first to write a review.

Write a Review

Alternatives to Consider

  • Google Cloud BigQuery Reviews & Ratings
    1,730 Ratings
    Company Website
  • DashboardFox Reviews & Ratings
    5 Ratings
    Company Website
  • Google AI Studio Reviews & Ratings
    4 Ratings
    Company Website
  • Fraud.net Reviews & Ratings
    56 Ratings
    Company Website
  • Qloo Reviews & Ratings
    23 Ratings
    Company Website
  • 6sense Reviews & Ratings
    1,597 Ratings
    Company Website
  • Vertex AI Reviews & Ratings
    673 Ratings
    Company Website
  • RunPod Reviews & Ratings
    116 Ratings
    Company Website
  • Quaeris Reviews & Ratings
    6 Ratings
    Company Website
  • Snowflake Reviews & Ratings
    1,389 Ratings
    Company Website

What is Salford Predictive Modeler (SPM)?

The Salford Predictive Modeler® (SPM) software suite is renowned for its remarkable speed and accuracy in crafting predictive, descriptive, or analytical models. Featuring engines such as CART®, TreeNet®, and Random Forests®, along with innovative automation capabilities and unique modeling functionalities, SPM stands out in the realm of data analysis tools. This comprehensive suite encompasses a range of data mining technologies, including classification, regression, survival analysis, and methods for handling missing values, as well as data binning and clustering. SPM algorithms are invaluable in sophisticated data science applications, making them a cornerstone for analysts seeking to derive insights from complex datasets. The automation of model construction is significantly streamlined with SPM, facilitating a more efficient exploration and refinement process. Furthermore, the suite allows for the seamless integration of results from various modeling approaches into a single, cohesive package, enhancing the review process for users. This combination of features not only boosts productivity but also empowers data professionals to make informed decisions more effectively.

What is MLlib?

MLlib, the machine learning component of Apache Spark, is crafted for exceptional scalability and seamlessly integrates with Spark's diverse APIs, supporting programming languages such as Java, Scala, Python, and R. It boasts a comprehensive array of algorithms and utilities that cover various tasks including classification, regression, clustering, collaborative filtering, and the construction of machine learning pipelines. By leveraging Spark's iterative computation capabilities, MLlib can deliver performance enhancements that surpass traditional MapReduce techniques by up to 100 times. Additionally, it is designed to operate across multiple environments, whether on Hadoop, Apache Mesos, Kubernetes, standalone clusters, or within cloud settings, while also providing access to various data sources like HDFS, HBase, and local files. This adaptability not only boosts its practical application but also positions MLlib as a formidable tool for conducting scalable and efficient machine learning tasks within the Apache Spark ecosystem. The combination of its speed, versatility, and extensive feature set makes MLlib an indispensable asset for data scientists and engineers striving for excellence in their projects. With its robust capabilities, MLlib continues to evolve, reinforcing its significance in the rapidly advancing field of machine learning.

Media

Media

Integrations Supported

Amazon EC2
Apache Cassandra
Apache HBase
Apache Hive
Apache Mesos
Apache Spark
Hadoop
Java
Kubernetes
MapReduce
Python
R
Scala

Integrations Supported

Amazon EC2
Apache Cassandra
Apache HBase
Apache Hive
Apache Mesos
Apache Spark
Hadoop
Java
Kubernetes
MapReduce
Python
R
Scala

API Availability

Has API

API Availability

Has API

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Company Facts

Organization Name

Minitab

Date Founded

1972

Company Location

United States

Company Website

www.minitab.com/en-us/products/spm/

Company Facts

Organization Name

Apache Software Foundation

Date Founded

1995

Company Location

United States

Company Website

spark.apache.org/mllib/

Categories and Features

Data Mining

Data Extraction
Data Visualization
Fraud Detection
Linked Data Management
Machine Learning
Predictive Modeling
Semantic Search
Statistical Analysis
Text Mining

Machine Learning

Deep Learning
ML Algorithm Library
Model Training
Natural Language Processing (NLP)
Predictive Modeling
Statistical / Mathematical Tools
Templates
Visualization

Predictive Analytics

AI / Machine Learning
Benchmarking
Data Blending
Data Mining
Demand Forecasting
For Education
For Healthcare
Modeling & Simulation
Sentiment Analysis

Categories and Features

Machine Learning

Deep Learning
ML Algorithm Library
Model Training
Natural Language Processing (NLP)
Predictive Modeling
Statistical / Mathematical Tools
Templates
Visualization

Popular Alternatives

MyDataModels TADA Reviews & Ratings

MyDataModels TADA

MyDataModels

Popular Alternatives

Apache Spark Reviews & Ratings

Apache Spark

Apache Software Foundation
TiMi Reviews & Ratings

TiMi

TIMi
Apache Mahout Reviews & Ratings

Apache Mahout

Apache Software Foundation
Orange Reviews & Ratings

Orange

University of Ljubljana