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What is Hopsworks?

Hopsworks is an all-encompassing open-source platform that streamlines the development and management of scalable Machine Learning (ML) pipelines, and it includes the first-ever Feature Store specifically designed for ML. Users can seamlessly move from data analysis and model development in Python, using tools like Jupyter notebooks and conda, to executing fully functional, production-grade ML pipelines without having to understand the complexities of managing a Kubernetes cluster. The platform supports data ingestion from diverse sources, whether they are located in the cloud, on-premises, within IoT networks, or are part of your Industry 4.0 projects. You can choose to deploy Hopsworks on your own infrastructure or through your preferred cloud service provider, ensuring a uniform user experience whether in the cloud or in a highly secure air-gapped environment. Additionally, Hopsworks offers the ability to set up personalized alerts for various events that occur during the ingestion process, which helps to optimize your workflow. This functionality makes Hopsworks an excellent option for teams aiming to enhance their ML operations while retaining oversight of their data environments, ultimately contributing to more efficient and effective machine learning practices. Furthermore, the platform's user-friendly interface and extensive customization options allow teams to tailor their ML strategies to meet specific needs and objectives.

What is Deepnote?

Deepnote is creating an exceptional data science notebook designed specifically for collaborative teams. You can seamlessly connect to your data, delve into analysis, and collaborate in real time while benefiting from version control. Additionally, you can easily share project links with fellow analysts and data scientists or showcase your refined notebooks to stakeholders and end users. This entire experience is facilitated through a robust, cloud-based user interface that operates directly in your browser, making it accessible and efficient for all. Ultimately, Deepnote aims to enhance productivity and streamline the data science workflow within teams.

Media

Media

Integrations Supported

Amazon EC2
Amazon Web Services (AWS)
IBM watsonx.data

Integrations Supported

Amazon Athena
Amazon Redshift
Amazon S3
Docker
Dropbox
GitHub
Google Cloud BigQuery
Google Cloud Container Security
Google Cloud Platform
Google Drive
MySQL
Reddit
Redshift
Telegram
neptune.ai

API Availability

API Availability

Pricing Information

$1 per month
Free Version
Free Trial Offered?

Pricing Information

Free
Starter: Free
Pro: $12/month
Enterprise: $99/month
Free Version

Supported Platforms

SaaS
On-Prem

Supported Platforms

SaaS

Customer Service / Support

Standard Support
Web-Based Support

Customer Service / Support

Web-Based Support

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Training Options

Documentation Hub

Company Facts

Organization Name

Logical Clocks

Date Founded

2016

Company Location

Sweden

Company Website

www.logicalclocks.com/hopsworks

Company Facts

Organization Name

Deepnote

Date Founded

2019

Company Location

United States

Company Website

deepnote.com

Categories and Features

Artificial Intelligence

For Healthcare
For eCommerce
Predictive Analytics
Process/Workflow Automation

Big Data

Collaboration
Data Cleansing
Data Mining
Data Visualization
Data Warehousing
High Volume Processing
Templates

Data Analysis

Data Discovery
Data Visualization
High Volume Processing
Regression Analysis

Data Management

Customer Data
Data Analysis
Data Integration
Data Migration
Data Quality Control
Data Security
Master Data Management

Machine Learning

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

Categories and Features

AI Data Analytics

Not specified

Artificial Intelligence

Machine Learning

Big Data

Collaboration
Data Visualization

Business Intelligence

Ad Hoc Reports
Data Analysis
Strategic Planning
Trend / Problem Indicators
Visual Analytics

Data Analysis

Data Visualization

Data Science

Advanced Modeling
Data Visualization
Model Deployment
Reports

Machine Learning

Deep Learning
Visualization

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