Average Ratings 0 Ratings
Average Ratings 0 Ratings
Description
Apache Ivy™ serves as a widely-used dependency manager that emphasizes both flexibility and ease of use. Discover its distinct enterprise capabilities, user feedback, and the ways it can enhance your build process! Ivy operates as a tool designed for the management of project dependencies, which includes recording, tracking, resolving, and reporting. It is not confined to any specific methodology or framework, allowing it to be highly adaptable to various dependency management and build workflows. Although it can function independently, Ivy is particularly effective in conjunction with Apache Ant, offering a variety of robust Ant tasks that range from resolving dependencies to generating reports and facilitating publication. Among its many powerful attributes, users often highlight its flexibility, seamless integration with Ant, and an efficient engine for managing transitive dependencies. Additionally, Ivy is an open-source tool, distributed under a permissive Apache License, making it accessible for a wide audience. This combination of features positions Ivy as a valuable asset for developers seeking to streamline their dependency management processes.
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
No
API Access
Has API
Yes
Integrations
Amazon EC2
No
Apache Ant
Yes
Apache Cassandra
No
Apache HBase
No
Apache Hive
No
Apache Mesos
No
Apache Spark
No
Hadoop
No
JFrog
Yes
Java
No
Integrations
Amazon EC2
Yes
Apache Ant
No
Apache Cassandra
Yes
Apache HBase
Yes
Apache Hive
Yes
Apache Mesos
Yes
Apache Spark
Yes
Hadoop
Yes
JFrog
No
Java
Yes
Pricing Details
Free
Free Trial
No
Free Version
Yes
Pricing Details
No price information available.
Free Trial
No
Free Version
No
Deployment
Web-Based
No
On-Premises
No
iPhone App
No
iPad App
No
Android App
No
Windows
Yes
Mac
Yes
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
No
Live Rep (24/7)
No
Online Support
Yes
Customer Support
Business Hours
Yes
Live Rep (24/7)
No
Online Support
Yes
Types of Training
Training Docs
Yes
Webinars
No
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
Apache Software Foundation
Country
United States
Website
ant.apache.org/ivy/
Vendor Details
Company Name
Apache Software Foundation
Founded
1995
Country
United States
Website
spark.apache.org/mllib/
Product Features
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