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Average Ratings 0 Ratings
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.
Description
Spark Cloud Studio is a cutting-edge cloud-based platform that provides efficient remote computing solutions, eliminating the necessity for powerful local hardware by offering immediate access to scalable virtual workstations, extensive secure storage, and on-demand CPU/GPU capabilities for rendering and computational tasks directly through your web browser or desktop application. Among its primary offerings are the Spark ProStation™ cloud workstations, which feature customizable hardware and come pre-equipped with essential creative and technical applications, Spark ShareSync™ for limitless encrypted file storage that includes real-time synchronization and versioning across multiple devices, and Spark SmartCompute™ that allows for scalable rendering farm resources to activate as needed for demanding workloads, along with a comprehensive creative toolkit ready for immediate use without any installation processes. The platform fosters collaboration by enabling real-time file sharing and efficient team management, seamlessly integrates with existing workflows and tools, and provides low-latency global access across a wide array of devices to ensure productivity is never hindered. Additionally, its user-friendly interface and robust features make it an ideal solution for creative professionals seeking flexibility and power in their projects.
API Access
Has API
Yes
API Access
Has API
No
Integrations
Python
Yes
Amazon EC2
Yes
Apache Cassandra
Yes
Apache Spark
Yes
Apple iOS
No
Clarisse iFX
No
FFmpeg
No
Katana
No
Kubernetes
Yes
LightWave 3D
No
Integrations
Python
Yes
Amazon EC2
No
Apache Cassandra
No
Apache Spark
No
Apple iOS
Yes
Clarisse iFX
Yes
FFmpeg
Yes
Katana
Yes
Kubernetes
No
LightWave 3D
Yes
Pricing Details
No price information available.
Free Trial
No
Free Version
No
Pricing Details
$0.99 per hour
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
Yes
iPad App
Yes
Android App
Yes
Windows
Yes
Mac
Yes
Linux
Yes
Chromebook
No
Customer Support
Business Hours
Yes
Live Rep (24/7)
No
Online Support
Yes
Customer Support
Business Hours
No
Live Rep (24/7)
No
Online Support
Yes
Types of Training
Training Docs
Yes
Webinars
Yes
Live Training (Online)
No
In Person
Yes
Types of Training
Training Docs
Yes
Webinars
No
Live Training (Online)
No
In Person
No
Vendor Details
Company Name
Apache Software Foundation
Founded
1995
Country
United States
Website
spark.apache.org/mllib/
Vendor Details
Company Name
Spark Cloud Studio
Founded
2023
Country
United States
Website
sparkcloud.studio/
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