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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
The primary obstacle in expanding AI-driven decision-making lies in the underutilization of data. IBM Cloud Pak® for Data provides a cohesive platform that integrates a data fabric, enabling seamless connection and access to isolated data, whether it resides on-premises or in various cloud environments, without necessitating data relocation. It streamlines data accessibility by automatically identifying and organizing data to present actionable knowledge assets to users, while simultaneously implementing automated policy enforcement to ensure secure usage. To further enhance the speed of insights, this platform incorporates a modern cloud data warehouse that works in harmony with existing systems. It universally enforces data privacy and usage policies across all datasets, ensuring compliance is maintained. By leveraging a high-performance cloud data warehouse, organizations can obtain insights more rapidly. Additionally, the platform empowers data scientists, developers, and analysts with a comprehensive interface to construct, deploy, and manage reliable AI models across any cloud infrastructure. Moreover, enhance your analytics capabilities with Netezza, a robust data warehouse designed for high performance and efficiency. This comprehensive approach not only accelerates decision-making but also fosters innovation across various sectors.
API Access
Has API
API Access
Has API
Integrations
Amazon EC2
Amazon Web Services (AWS)
Datamatics Trade Finance
IBM Control Desk
IBM Db2 Big SQL
IBM Db2 Event Store
IBM InfoSphere Information Governance Catalog
IBM Netezza Performance Server
IBM Storage Software Suite
IBM WebSphere Commerce
Integrations
Amazon EC2
Amazon Web Services (AWS)
Datamatics Trade Finance
IBM Control Desk
IBM Db2 Big SQL
IBM Db2 Event Store
IBM InfoSphere Information Governance Catalog
IBM Netezza Performance Server
IBM Storage Software Suite
IBM WebSphere Commerce
Pricing Details
$1 per month
Free Trial
Free Version
Pricing Details
$699 per month
Free Trial
Free Version
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Vendor Details
Company Name
Logical Clocks
Founded
2016
Country
Sweden
Website
www.logicalclocks.com/hopsworks
Vendor Details
Company Name
IBM
Founded
1911
Country
United States
Website
www.ibm.com/products/cloud-pak-for-data
Product Features
Artificial Intelligence
Chatbot
For Healthcare
For Sales
For eCommerce
Image Recognition
Machine Learning
Multi-Language
Natural Language Processing
Predictive Analytics
Process/Workflow Automation
Rules-Based Automation
Virtual Personal Assistant (VPA)
Big Data
Collaboration
Data Blends
Data Cleansing
Data Mining
Data Visualization
Data Warehousing
High Volume Processing
No-Code Sandbox
Predictive Analytics
Templates
Data Analysis
Data Discovery
Data Visualization
High Volume Processing
Predictive Analytics
Regression Analysis
Sentiment Analysis
Statistical Modeling
Text Analytics
Data Management
Customer Data
Data Analysis
Data Capture
Data Integration
Data Migration
Data Quality Control
Data Security
Information Governance
Master Data Management
Match & Merge
Machine Learning
Deep Learning
ML Algorithm Library
Model Training
Natural Language Processing (NLP)
Predictive Modeling
Statistical / Mathematical Tools
Templates
Visualization
Product Features
Big Data
Collaboration
Data Blends
Data Cleansing
Data Mining
Data Visualization
Data Warehousing
High Volume Processing
No-Code Sandbox
Predictive Analytics
Templates
Data Fabric
Data Access Management
Data Analytics
Data Collaboration
Data Lineage Tools
Data Networking / Connecting
Metadata Functionality
No Data Redundancy
Persistent Data Management
Data Science
Access Control
Advanced Modeling
Audit Logs
Data Discovery
Data Ingestion
Data Preparation
Data Visualization
Model Deployment
Reports
Machine Learning
Deep Learning
ML Algorithm Library
Model Training
Natural Language Processing (NLP)
Predictive Modeling
Statistical / Mathematical Tools
Templates
Visualization
Predictive Analytics
AI / Machine Learning
Benchmarking
Data Blending
Data Mining
Demand Forecasting
For Education
For Healthcare
Modeling & Simulation
Sentiment Analysis