Jupyter Notebook

Jupyter Notebook

Project Jupyter
+

Related Products

  • Google Cloud BigQuery
    2,017 Ratings
    Visit Website
  • Teradata VantageCloud
    1,122 Ratings
    Visit Website
  • DbVisualizer
    583 Ratings
    Visit Website
  • Gemini Enterprise Agent Platform
    984 Ratings
    Visit Website
  • DataBuck
    6 Ratings
    Visit Website
  • Qloo
    23 Ratings
    Visit Website
  • Fraud.net
    56 Ratings
    Visit Website
  • Harmoni
    16 Ratings
    Visit Website
  • SciSure
    299 Ratings
    Visit Website
  • dbt
    263 Ratings
    Visit Website

About

Deepnote is building the best data science notebook for teams. In the notebook, users can connect their data, explore, and analyze it with real-time collaboration and version control. Users can easily share project links with team collaborators, or with end-users to present polished assets. All of this is done through a powerful, browser-based UI that runs in the cloud. We built Deepnote because data scientists don't work alone. Features: - Sharing notebooks and projects via URL - Inviting others to view, comment and collaborate, with version control - Publishing notebooks with visualizations for presentations - Sharing datasets between projects - Set team permissions to decide who can edit vs view code - Full linux terminal access - Code completion - Automatic python package management - Importing from github - PostgreSQL DB connection

About

Hex brings together the best of notebooks, BI, and docs into a seamless, collaborative UI. Hex is a modern Data Workspace. It makes it easy to connect to data, analyze it in collaborative SQL and Python-powered notebooks, and share work as interactive data apps and stories. Your default landing page in Hex is the Projects page. You can quickly find projects you created, as well as those shared with you and your workspace. The outline provides an easy-to-browse overview of all the cells in a project's Logic View. Every cell in the outline lists the variables it defines, and cells that return a displayed output (chart cells, Input Parameters, markdown cells, etc.) display a preview of that output. You can click any cell in the outline to automatically jump to that position in the logic.

About

The Jupyter Notebook is an open-source web application that allows you to create and share documents that contain live code, equations, visualizations and narrative text. Uses include: data cleaning and transformation, numerical simulation, statistical modeling, data visualization, machine learning, and much more.

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Audience

Enterprises and teams interested in a data science notebook solution to make data science teams more productive

Audience

Individuals in need of a collaborative data platform

Audience

Anyone who wants to create and share documents that contain live code, equations, visualizations and narrative text

Support

Phone Support
24/7 Live Support
Online

Support

Phone Support
24/7 Live Support
Online

Support

Phone Support
24/7 Live Support
Online

API

Offers API

API

Offers API

API

Offers API

Screenshots and Videos

Screenshots and Videos

Screenshots and Videos

Pricing

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

Pricing

$24 per user per month
Free Version
Free Trial

Pricing

No information available.
Free Version
Free Trial

Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

This software hasn't been reviewed yet. Be the first to provide a review:

Review this Software

Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

This software hasn't been reviewed yet. Be the first to provide a review:

Review this Software

Reviews/Ratings

Overall 5.0 / 5
ease 5.0 / 5
features 5.0 / 5
design 4.0 / 5
support 4.5 / 5

Pros & Cons from Real Users

Pros

  • Step-by-step casual coders like me dream of such a simple software. I use the tool to execute simple Python scripts and Jupyter is far easier to code on that Visual Studio or even the Python shell itself. Keyboard shortcuts make it even easier to use.
  • • It is web-based, so saves you a lot of space. • Allows you to import your own code in many formats. • You can also work with visuals and charts. • I like that you can code line-by-line or all at once with ctrl + Enter shortcut, which is very useful for debugging. • Mostly, I like that it is also a great tool for teaching and practicing machine learning.

Cons

  • Would be better if installation is easier. I had to watch a few YouTube videos to understand how to start installation.
  • • It gets buggy at times, and takes some time to load initially. • Can be slow even on high speed networks. • The interface is pretty old fashioned.

Training

Documentation
Webinars
Live Online
In Person

Training

Documentation
Webinars
Live Online
In Person

Training

Documentation
Webinars
Live Online
In Person

Company Information

Deepnote
Founded: 2019
United States
deepnote.com

Company Information

Hex
hex.tech/

Company Information

Project Jupyter
Founded: 2014
jupyter.org

Alternatives

Alternatives

Alternatives

Azure Notebooks

Azure Notebooks

Microsoft
JupyterLab

JupyterLab

Jupyter

Categories

Categories

Categories

Data Science Features

Access Control
Advanced Modeling
Audit Logs
Data Discovery
Data Ingestion
Data Preparation
Data Visualization
Model Deployment
Reports

Artificial Intelligence Features

Chatbot
For eCommerce
For Healthcare
For Sales
Image Recognition
Machine Learning
Multi-Language
Natural Language Processing
Predictive Analytics
Process/Workflow Automation
Rules-Based Automation
Virtual Personal Assistant (VPA)

Big Data Features

Collaboration
Data Blends
Data Cleansing
Data Mining
Data Visualization
Data Warehousing
High Volume Processing
No-Code Sandbox
Predictive Analytics
Templates

Business Intelligence Features

Ad Hoc Reports
Benchmarking
Budgeting & Forecasting
Dashboard
Data Analysis
Key Performance Indicators
Natural Language Generation (NLG)
Performance Metrics
Predictive Analytics
Profitability Analysis
Strategic Planning
Trend / Problem Indicators
Visual Analytics

Data Analysis Features

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

Data Visualization Features

Analytics
Content Management
Dashboard Creation
Filtered Views
OLAP
Relational Display
Simulation Models
Visual Discovery

Machine Learning Features

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

Integrations

GitHub
Akira AI
Betteromics
Coding Rooms
Coiled
DagsHub
Datafi
EdgeCortix
Google Cloud Container Security
Google Cloud Datalab
JupyterHub
Lambda
Modelbit
NVIDIA Morpheus
Snowflake
TwinThread
Weights & Biases
dbt
lakeFS

Integrations

GitHub
Akira AI
Betteromics
Coding Rooms
Coiled
DagsHub
Datafi
EdgeCortix
Google Cloud Container Security
Google Cloud Datalab
JupyterHub
Lambda
Modelbit
NVIDIA Morpheus
Snowflake
TwinThread
Weights & Biases
dbt
lakeFS

Integrations

GitHub
Akira AI
Betteromics
Coding Rooms
Coiled
DagsHub
Datafi
EdgeCortix
Google Cloud Container Security
Google Cloud Datalab
JupyterHub
Lambda
Modelbit
NVIDIA Morpheus
Snowflake
TwinThread
Weights & Biases
dbt
lakeFS
Claim Deepnote and update features and information
Claim Deepnote and update features and information
Claim Hex and update features and information
Claim Hex and update features and information
Claim Jupyter Notebook and update features and information
Claim Jupyter Notebook and update features and information