Average Ratings 2 Ratings

Total
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Average Ratings 0 Ratings

Total
ease
features
design
support

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Description

The Jupyter Notebook is a web-based open-source tool that enables users to create and distribute documents featuring live code, visualizations, equations, and written explanations. Its applications are diverse and encompass tasks such as data cleaning and transformation, statistical modeling, numerical simulations, data visualization, machine learning, among others, showcasing its versatility in various fields. Additionally, it serves as an excellent platform for collaboration and sharing insights within the data science community.

Description

This desktop application integrates Jupyter Notebook and Python, allowing for a seamless one-click installation. It features engaging code snippets alongside an AI assistant that enhances coding efficiency, making it an ideal tool for data science endeavors. We have meticulously developed over 100 interactive code recipes tailored for your Data Science projects, which can identify available packages within your current environment. With a single click, you can install any required modules, streamlining your workflow significantly. Users can easily create and manipulate all variables present in their Python session, while these interactive recipes expedite the completion of tasks. The AI Assistant, equipped with knowledge of your active Python session, variables, and modules, is designed to address data challenges using the Python programming language. It offers support for various tasks, including plotting, data loading, data wrangling, and machine learning. If you encounter code issues, simply click the Fix button, and the AI assistant will analyze the problem and suggest a viable solution, making your coding experience smoother and more productive. Additionally, this innovative tool not only simplifies coding but also enhances your learning curve in data science.

API Access

Has API No 

API Access

Has API No 

Screenshots View All

Screenshots View All

Integrations

GitHub Yes 
Stata Yes 
3LC Yes 
CodeSquire Yes 
Datameer Yes 
Forloop Yes 
Fuzzball Yes 
GeoSpock Yes 
Gradient Yes 
JupyterHub Yes 
LSEG Workspace Yes 
Molecula Yes 
Moonglow Yes 
PayPal No 
Sharon AI Yes 
Thunder Compute Yes 
Vectice Yes 
lakeFS Yes 
packet.ai Yes 

Integrations

GitHub Yes 
Stata Yes 
3LC No 
CodeSquire No 
Datameer No 
Forloop No 
Fuzzball No 
GeoSpock No 
Gradient No 
JupyterHub No 
LSEG Workspace No 
Molecula No 
Moonglow No 
PayPal Yes 
Sharon AI No 
Thunder Compute No 
Vectice No 
lakeFS No 
packet.ai No 

Pricing Details

No price information available.
Free Trial No 
Free Version Yes 

Pricing Details

$20 per month
Free Trial No 
Free Version Yes 

Deployment

Web-Based Yes 
On-Premises No 
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 Yes 
Mac Yes 
Linux Yes 
Chromebook No 

Customer Support

Business Hours No 
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 No 
Live Training (Online) No 
In Person No 

Types of Training

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

Vendor Details

Company Name

Project Jupyter

Founded

2014

Website

jupyter.org

Vendor Details

Company Name

MLJAR

Founded

2016

Country

Poland

Website

mljar.com

Product Features

Application Development

Access Controls/Permissions No 
Code Assistance No 
Code Refactoring No 
Collaboration Tools No 
Compatibility Testing No 
Data Modeling No 
Debugging No 
Deployment Management No 
Graphical User Interface No 
Mobile Development No 
No-Code No 
Reporting/Analytics No 
Software Development No 
Source Control No 
Testing Management No 
Version Control No 
Web App Development No 

Data Science

Access Control No 
Advanced Modeling No 
Audit Logs No 
Data Discovery No 
Data Ingestion No 
Data Preparation No 
Data Visualization No 
Model Deployment No 
Reports No 

Product Features

Data Science

Access Control No 
Advanced Modeling No 
Audit Logs No 
Data Discovery No 
Data Ingestion No 
Data Preparation No 
Data Visualization No 
Model Deployment No 
Reports No 

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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