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Average Ratings 0 Ratings

Total
ease
features
design
support

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Write a Review

Description

The Code Ocean Computational Workbench enhances usability, coding, data tool integration, and DevOps lifecycle processes by bridging technology gaps with a user-friendly, ready-to-use interface. It provides readily accessible tools like RStudio, Jupyter, Shiny, Terminal, and Git, while allowing users to select from a variety of popular programming languages. Users can access diverse data sizes and storage types, configure, and generate Docker environments with ease. Furthermore, it offers one-click access to AWS compute resources, streamlining workflows significantly. Through the app panel of the Code Ocean Computational Workbench, researchers can effortlessly share findings by creating and publishing user-friendly web analysis applications for teams of scientists, all without needing IT support, coding skills, or command-line proficiency. This platform allows for the creation and deployment of interactive analyses that operate seamlessly in standard web browsers. Collaboration and sharing of results are simplified, and resources can be reused and managed with minimal effort. By providing a straightforward application and repository, researchers can efficiently organize, publish, and safeguard project-based Compute Capsules, data assets, and their research outcomes, ultimately promoting a more collaborative and productive research environment. The versatility and ease of use of this workbench make it an invaluable tool for scientists looking to enhance their research capabilities.

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

API Access

Has API

Screenshots View All

Screenshots View All

Integrations

Docker
Jupyter Notebook
Arize Phoenix
Azure Marketplace
Baidu AI Cloud Machine Learning (BML)
CSS
CodeSquire
Fosfor Decision Cloud
Google Cloud Deep Learning VM Image
HTML
Intel Open Edge Platform
JarvisLabs.ai
JetBrains DataSpell
Kubernetes
OAuth
Python
Scala
Scheme
Thunder Compute

Integrations

Docker
Jupyter Notebook
Arize Phoenix
Azure Marketplace
Baidu AI Cloud Machine Learning (BML)
CSS
CodeSquire
Fosfor Decision Cloud
Google Cloud Deep Learning VM Image
HTML
Intel Open Edge Platform
JarvisLabs.ai
JetBrains DataSpell
Kubernetes
OAuth
Python
Scala
Scheme
Thunder Compute

Pricing Details

No price information available.
Free Trial
Free Version

Pricing Details

No price information available.
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

Code Ocean

Country

United States

Website

codeocean.com/product/

Vendor Details

Company Name

Jupyter

Founded

2014

Website

jupyter.org

Product Features

Data Analysis

Data Discovery
Data Visualization
High Volume Processing
Predictive Analytics
Regression Analysis
Sentiment Analysis
Statistical Modeling
Text Analytics

Product Features

IDE

Code Completion
Compiler
Cross Platform Support
Debugger
Drag and Drop UI
Integrations and Plugins
Multi Language Support
Project Management
Text Editor / Code Editor

Alternatives

R Markdown Reviews

R Markdown

RStudio PBC

Alternatives

Jupyter Notebook Reviews

Jupyter Notebook

Project Jupyter