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features
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support

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Description

Hopsworks is a comprehensive open-source platform designed to facilitate the creation and management of scalable Machine Learning (ML) pipelines, featuring the industry's pioneering Feature Store for ML. Users can effortlessly transition from data analysis and model creation in Python, utilizing Jupyter notebooks and conda, to executing robust, production-ready ML pipelines without needing to acquire knowledge about managing a Kubernetes cluster. The platform is capable of ingesting data from a variety of sources, whether they reside in the cloud, on-premise, within IoT networks, or stem from your Industry 4.0 initiatives. You have the flexibility to deploy Hopsworks either on your own infrastructure or via your chosen cloud provider, ensuring a consistent user experience regardless of the deployment environment, be it in the cloud or a highly secure air-gapped setup. Moreover, Hopsworks allows you to customize alerts for various events triggered throughout the ingestion process, enhancing your workflow efficiency. This makes it an ideal choice for teams looking to streamline their ML operations while maintaining control over their data environments.

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 

Screenshots View All

Screenshots View All

Integrations

Amazon EC2 Yes 
Amazon Web Services (AWS) Yes 
Apache Cassandra No 
Apache HBase No 
Apache Hive No 
Apache Mesos No 
Apache Spark No 
Hadoop No 
IBM watsonx.data Yes 
Java No 
Kubernetes No 
MapReduce No 
Onehouse Yes 
Python No 
R No 
Scala No 

Integrations

Amazon EC2 Yes 
Amazon Web Services (AWS) No 
Apache Cassandra Yes 
Apache HBase Yes 
Apache Hive Yes 
Apache Mesos Yes 
Apache Spark Yes 
Hadoop Yes 
IBM watsonx.data No 
Java Yes 
Kubernetes Yes 
MapReduce Yes 
Onehouse No 
Python Yes 
R Yes 
Scala Yes 

Pricing Details

$1 per month
Free Trial Yes 
Free Version Yes 

Pricing Details

No price information available.
Free Trial No 
Free Version No 

Deployment

Web-Based Yes 
On-Premises Yes 
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 No 
iPad App No 
Android App No 
Windows No 
Mac No 
Linux No 
Chromebook No 

Customer Support

Business Hours Yes 
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 Yes 
Live Training (Online) Yes 
In Person Yes 

Types of Training

Training Docs Yes 
Webinars Yes 
Live Training (Online) No 
In Person Yes 

Vendor Details

Company Name

Logical Clocks

Founded

2016

Country

Sweden

Website

www.logicalclocks.com/hopsworks

Vendor Details

Company Name

Apache Software Foundation

Founded

1995

Country

United States

Website

spark.apache.org/mllib/

Product Features

Artificial Intelligence

Chatbot No 
For Healthcare Yes 
For Sales No 
For eCommerce Yes 
Image Recognition No 
Machine Learning No 
Multi-Language No 
Natural Language Processing No 
Predictive Analytics Yes 
Process/Workflow Automation Yes 
Rules-Based Automation No 
Virtual Personal Assistant (VPA) No 

Big Data

Collaboration Yes 
Data Blends No 
Data Cleansing Yes 
Data Mining Yes 
Data Visualization Yes 
Data Warehousing Yes 
High Volume Processing Yes 
No-Code Sandbox No 
Predictive Analytics No 
Templates Yes 

Data Analysis

Data Discovery Yes 
Data Visualization Yes 
High Volume Processing Yes 
Predictive Analytics No 
Regression Analysis Yes 
Sentiment Analysis No 
Statistical Modeling No 
Text Analytics No 

Data Management

Customer Data Yes 
Data Analysis Yes 
Data Capture No 
Data Integration Yes 
Data Migration Yes 
Data Quality Control Yes 
Data Security Yes 
Information Governance No 
Master Data Management Yes 
Match & Merge No 

Machine Learning

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

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 

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