TrustRadius Insights
Users of Apache Mahout have found value in the software for a range of business problems. With its ability to create machine learning …
Overview
What is Apache Mahout?
Apache Mahout is a distributed linear algebra framework designed to let mathematicians, statisticians, and data scientists implement their own algorithms.
Recent Reviews
Leaving a review helps other professionals like you evaluate Machine Learning Tools
Be the first one in your network to review Apache Mahout, and make your voice heard!
Get StartedPricing
N/A
Unavailable
What is Apache Mahout?
Apache Mahout is a distributed linear algebra framework designed to let mathematicians, statisticians, and data scientists implement their own algorithms.
Entry-level set up fee?
- No setup fee
Offerings
- Free Trial
- Free/Freemium Version
- Premium Consulting/Integration Services
Would you like us to let the vendor know that you want pricing?
3 people also want pricing
Alternatives Pricing
N/A
Unavailable
What is Dataiku?
Dataiku is a French startup and its product, DSS, is a challenger to market incumbents and features some visual tools to assist in building workflows.
What is Qlik Sense?
Qlik Sense® is a self-service BI platform for data discovery and visualization. It supports a full range of analytics use cases—data governance, pixel-perfect reporting, and collaboration. Its Associative Engine indexes and connects relationships between data points for creating actionable insights.
Product Demos
Apache Mahout Demo of Classification
YouTube
Product Details
- About
- Tech Details
What is Apache Mahout?
Apache Mahout is a distributed linear algebra framework designed to let mathematicians, statisticians, and data scientists implement their own algorithms.
Apache Mahout Technical Details
| Operating Systems | Unspecified |
|---|---|
| Mobile Application | No |
Comparisons
Compare with
Reviews
Community Insights
TrustRadius Insights are summaries of user sentiment data from TrustRadius reviews and, when necessary, 3rd-party data sources. Have feedback on this content? Let us know!
- Business Problems Solved
- Pros
- Cons
Users of Apache Mahout have found value in the software for a range of business problems. With its ability to create machine learning algorithms, Mahout has been instrumental in solving various tasks such as recommendation, classification, and clustering. For example, users have successfully used Mahout to develop models on large-scale datasets, providing solutions for data storage management and addressing data consistency issues in financial work. Furthermore, Mahout's integration with compatible libraries like MLLib has enabled tasks such as salary matrices filtering or book and movie recommendations on dating sites, saving time and reducing the need for additional personnel. Its user-friendly features have made it suitable for data processing and mining, allowing users to perform statistical analysis on large datasets generated from work item export tools. Additionally, Mahout has been used for building models on large-scale traffic data, analyzing traffic patterns and anomalies. Users have also found value in Mahout for comparative analysis between different machine learning frameworks to help decide which framework is best suited for their needs. Overall, Apache Mahout provides an effective solution for processing and testing large-scale data on machine learning algorithms, enabling users to solve critical business problems efficiently.
Scalable and Easy to Use: Reviewers have consistently praised Apache Mahout for being a scalable machine learning library that is also easy to use. Many users have found it unique in its ability to handle large datasets, with some mentioning developing machine learning models on more than 10 million datasets. This makes Mahout a valuable tool for engineers, mathematicians, and statisticians looking to work on their hypothesis models and perform computations efficiently.
Great Tool for Financial Workflows: Users have highlighted Mahout's capabilities in handling financial workflows. The software allows users to run summary statistics as well as more advanced statistics like linear correlation and autocorrelation to detect discrepancies in financial data. This feature has been appreciated by reviewers who rely on Mahout for analyzing financial information accurately.
Extensible Programming Framework: One of the standout features of Apache Mahout is its access to an extensible programming framework, enabling users to build scalable algorithms. Multiple reviewers have mentioned how this feature enhances the flexibility of the software, allowing them to develop and deploy large-scale machine learning algorithms using relatively short lines of code.
-
Steep learning curve: Some users have found Mahout to be challenging to use due to its requirement for prior expertise in machine learning and the tool itself. This can be a disadvantage for users who are not already familiar with these areas.
-
Limited algorithm coverage: A few reviewers have mentioned that Mahout does not cover all kinds of algorithms, which may limit its usability for certain tasks. This could be a drawback for users who require specific algorithms that are not supported by Mahout.
-
Lack of enterprise support and limited knowledge repository: The lack of enterprise support and limited online knowledge repository were highlighted as potential downsides of Mahout. Users have expressed concerns about the absence of dedicated support for resolving issues or accessing comprehensive documentation when using this open-source framework.