Jupyter Notebook vs. Obviously AI

Overview
ProductRatingMost Used ByProduct SummaryStarting Price
Jupyter Notebook
Score 9.4 out of 10
N/A
Jupyter Notebook is an open-source web application that allows users to create and share documents containing live code, equations, visualizations and narrative text. Uses include: data cleaning and transformation, numerical simulation, statistical modeling, data visualization, and machine learning. It supports over 40 programming languages, and notebooks can be shared with others using email, Dropbox, GitHub and the Jupyter Notebook Viewer. It is used with JupyterLab, a web-based IDE for…N/A
Obviously AI
Score 0.0 out of 10
N/A
Obviously AI offers their solution to allow users to create AI models without code, such as classification models (e.g. fraud detection, lead conversion, churn), regression models (predicting sales, dynamic pricing, etc.), or time series to predict the occurrence of future events of interest. Obviously AI offers self-service plans, and higher tier plans include support from a dedicated data scientist who joins the customer's team to produce models, with code files available on higher tier plans.
$300
per month 1 user & 12,000 predictions
Pricing
Jupyter NotebookObviously AI
Editions & Modules
No answers on this topic
Limited Access
$300
per month 1 user & 12,000 predictions
Full Access
$999
per month 5 user seats & 120,000 predictions
Data Scientist
$999
per month unlimited requests and revisions
Data Scientist with Code Files
$1999
per month unlimited requests and revisions
Data Scientist Team with Express Support
Custom Plan
Offerings
Pricing Offerings
Jupyter NotebookObviously AI
Free Trial
NoYes
Free/Freemium Version
NoYes
Premium Consulting/Integration Services
NoNo
Entry-level Setup FeeNo setup feeNo setup fee
Additional Details
More Pricing Information
Community Pulse
Jupyter NotebookObviously AI
Features
Jupyter NotebookObviously AI
Platform Connectivity
Comparison of Platform Connectivity features of Product A and Product B
Jupyter Notebook
9.0
Ratings
7% above category average
Obviously AI
-
Ratings
Connect to Multiple Data Sources10.00 Ratings00 Ratings
Extend Existing Data Sources10.00 Ratings00 Ratings
Automatic Data Format Detection8.50 Ratings00 Ratings
MDM Integration7.40 Ratings00 Ratings
Data Exploration
Comparison of Data Exploration features of Product A and Product B
Jupyter Notebook
7.0
Ratings
18% below category average
Obviously AI
-
Ratings
Visualization6.00 Ratings00 Ratings
Interactive Data Analysis8.00 Ratings00 Ratings
Data Preparation
Comparison of Data Preparation features of Product A and Product B
Jupyter Notebook
9.5
Ratings
15% above category average
Obviously AI
-
Ratings
Interactive Data Cleaning and Enrichment10.00 Ratings00 Ratings
Data Transformations10.00 Ratings00 Ratings
Data Encryption8.50 Ratings00 Ratings
Built-in Processors9.30 Ratings00 Ratings
Platform Data Modeling
Comparison of Platform Data Modeling features of Product A and Product B
Jupyter Notebook
9.3
Ratings
10% above category average
Obviously AI
-
Ratings
Multiple Model Development Languages and Tools10.00 Ratings00 Ratings
Automated Machine Learning9.20 Ratings00 Ratings
Single platform for multiple model development10.00 Ratings00 Ratings
Self-Service Model Delivery8.00 Ratings00 Ratings
Model Deployment
Comparison of Model Deployment features of Product A and Product B
Jupyter Notebook
10.0
Ratings
16% above category average
Obviously AI
-
Ratings
Flexible Model Publishing Options10.00 Ratings00 Ratings
Security, Governance, and Cost Controls10.00 Ratings00 Ratings
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Jupyter NotebookObviously AI
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Score 10.0 out of 10
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Score 10.0 out of 10
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User Ratings
Jupyter NotebookObviously AI
Likelihood to Recommend
10.0
(0 ratings)
-
(0 ratings)
Usability
10.0
(0 ratings)
-
(0 ratings)
Support Rating
9.0
(0 ratings)
-
(0 ratings)
User Testimonials
Jupyter NotebookObviously AI
Likelihood to Recommend
I would rate it 9/10 while recommending Jupyter Notebook as it offers me a wide range of functionality to operate. It is very well suited for someone who is new to python programming as the user interface helps you build code line by line. I personally have written multiple programs in Python using Jupyter Notebook as it helps me organize long code by breaking it in a structure. Also the ability to write comments using '#' helps a lot to a reader understand the code.
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No answers on this topic
Pros
  • Coding and error correction line by line
  • Simple and Effectiveness
  • Easy to use for visualisation and presentation of code
  • Could be used at any place any time without hassle
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No answers on this topic
Cons
  • Need more Hotkeys for creating a beautiful notebook. Sometimes we need to download other plugins which messes [with] its default settings.
  • Not as powerful as IDE, which sometimes makes [the] job difficult and allows duplicate code as it get confusing when the number of lines increases. Need a feature where [an] error comes if duplicate code is found or [if a] developer tries the same function name.
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Usability
Jupyter is highly simplistic. It took me about 5 mins to install and create my first "hello world" without having to look for help. The UI has minimalist options and is quite intuitive for anyone to become a pro in no time. The lightweight nature makes it even more likeable.
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No answers on this topic
Support Rating
I haven't had a need to contact support. However, all required help is out there in public forums.
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Alternatives Considered
Jupyter Notebook is unique in that it offers a flexible, lightweight, easy-to-replicate way of organizing your code in a visually intuitive fashion that can be exported in a number of formats. I've found that the broad functionalities available within the notebooks suit a lot of needs I have for EDA, modeling, and data export that makes other software products fairly redundant.
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Return on Investment
  • Positive impact: flexible implementation on any OS, for many common software languages
  • Positive impact: straightforward duplication for adaptation of workflows for other projects
  • Negative impact: sometimes encourages pigeonholing of data science work into notebooks versus extending code capability into software integration
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ScreenShots