Project Summary
Apache Mahout's goal is to build scalable machine learning libraries. With scalable we mean:
Scalable to reasonably large data sets. Our core algorithms for clustering, classfication and batch based collaborative filtering are implemented on top of Apache Hadoop using the map/reduce paradigm. However we do not restrict contributions to Hadoop based implementations: Contributions that run on a single node or on a non-Hadoop cluster are welcome as well. The core libraries are highly optimized to allow for good performance also for non-distributed algorithms
In a Nutshell, Apache Mahout...
- ...
- ...
-
...
has a well established, mature codebase
maintained by a small development team
with decreasing Y-O-Y commits -
...
took an estimated 38 years of effort (COCOMO model)
starting with its first commit in January, 2008
ending with its most recent commit 2 months ago
Quick Reference
Apache License 2.0
Permitted
Commercial Use
Modify
Distribute
Place Warranty
Sub-License
Private Use
Use Patent Claims
Forbidden
Hold Liable
Use Trademarks
Required
Include Copyright
State Changes
Include License
Include Notice
These details are provided for information only. No information here is legal advice and should not be used as such.
Project Security
Vulnerabilities per Version ( last 10 releases )
There are no reported vulnerabilities
Project Vulnerability Report
Security Confidence Index
Vulnerability Exposure Index
Did You Know...
-
...
nearly 1 in 3 companies have no process for identifying, tracking, or remediating known open source vulnerabilities
-
...
check out hot projects on the Open Hub
-
...
55% of companies leverage OSS for production infrastructure
-
...
learn about Open Hub updates and features on the Open Hub blog
30 Day SummaryMar 24 2024 — Apr 23 2024
|
12 Month SummaryApr 23 2023 — Apr 23 2024
|
