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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
Project Jupyter is dedicated to the creation of open-source tools, standards, and services that facilitate interactive computing in numerous programming languages. At the heart of this initiative is JupyterLab, a web-based interactive development environment designed for Jupyter notebooks, coding, and data manipulation. JupyterLab offers remarkable flexibility, allowing users to customize and organize the interface to cater to various workflows in fields such as data science, scientific research, and machine learning. Its extensibility and modular nature enable developers to create plugins that introduce new features and seamlessly integrate with existing components. The Jupyter Notebook serves as an open-source web application enabling users to produce and share documents that incorporate live code, mathematical equations, visualizations, and descriptive text. Common applications of Jupyter include data cleaning and transformation, numerical simulations, statistical analysis, data visualization, and machine learning, among others. Supporting over 40 programming languages—including popular ones like Python, R, Julia, and Scala—Jupyter continues to be a valuable resource for researchers and developers alike, fostering collaborative and innovative approaches to computing challenges.
API Access
Has API
No
API Access
Has API
No
Integrations
AWS Marketplace
No
Amazon EC2
Yes
Arize Phoenix
No
Azure Marketplace
No
CodeSquire
No
Fosfor Decision Cloud
No
Google Cloud Deep Learning VM Image
No
IBM watsonx.data
Yes
Illumina Connected Analytics
No
JetBrains DataSpell
No
Integrations
AWS Marketplace
Yes
Amazon EC2
No
Arize Phoenix
Yes
Azure Marketplace
Yes
CodeSquire
Yes
Fosfor Decision Cloud
Yes
Google Cloud Deep Learning VM Image
Yes
IBM watsonx.data
No
Illumina Connected Analytics
Yes
JetBrains DataSpell
Yes
Pricing Details
$1 per month
Free Trial
Yes
Free Version
Yes
Pricing Details
No price information available.
Free Trial
Yes
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
No
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
No
Live Training (Online)
No
In Person
No
Vendor Details
Company Name
Logical Clocks
Founded
2016
Country
Sweden
Website
www.logicalclocks.com/hopsworks
Vendor Details
Company Name
Jupyter
Founded
2014
Website
jupyter.org
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
