Appen vs. Jupyter Notebook

Overview
ProductRatingMost Used ByProduct SummaryStarting Price
Appen
Score 7.1 out of 10
N/A
The Appen platform combines human intelligence from over one million people all over the world with models to create training data for ML projects. Appen users can upload data to the Appen platform, and they provide the annotations, judgments, and labels needed to help create ground truth for models.N/A
Jupyter Notebook
Score 8.9 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
Pricing
AppenJupyter Notebook
Editions & Modules
No answers on this topic
No answers on this topic
Offerings
Pricing Offerings
AppenJupyter Notebook
Free Trial
NoNo
Free/Freemium Version
NoNo
Premium Consulting/Integration Services
NoNo
Entry-level Setup FeeNo setup feeNo setup fee
Additional Details
More Pricing Information
Community Pulse
AppenJupyter Notebook
Top Pros

No answers on this topic

Top Cons

No answers on this topic

Features
AppenJupyter Notebook
Platform Connectivity
Comparison of Platform Connectivity features of Product A and Product B
Appen
-
Ratings
Jupyter Notebook
8.5
21 Ratings
1% above category average
Connect to Multiple Data Sources00 Ratings9.021 Ratings
Extend Existing Data Sources00 Ratings9.220 Ratings
Automatic Data Format Detection00 Ratings8.514 Ratings
MDM Integration00 Ratings7.415 Ratings
Data Exploration
Comparison of Data Exploration features of Product A and Product B
Appen
-
Ratings
Jupyter Notebook
9.6
21 Ratings
13% above category average
Visualization00 Ratings9.621 Ratings
Interactive Data Analysis00 Ratings9.621 Ratings
Data Preparation
Comparison of Data Preparation features of Product A and Product B
Appen
-
Ratings
Jupyter Notebook
9.0
21 Ratings
9% above category average
Interactive Data Cleaning and Enrichment00 Ratings9.320 Ratings
Data Transformations00 Ratings8.921 Ratings
Data Encryption00 Ratings8.514 Ratings
Built-in Processors00 Ratings9.314 Ratings
Platform Data Modeling
Comparison of Platform Data Modeling features of Product A and Product B
Appen
-
Ratings
Jupyter Notebook
8.9
21 Ratings
5% above category average
Multiple Model Development Languages and Tools00 Ratings9.020 Ratings
Automated Machine Learning00 Ratings9.218 Ratings
Single platform for multiple model development00 Ratings9.221 Ratings
Self-Service Model Delivery00 Ratings8.020 Ratings
Model Deployment
Comparison of Model Deployment features of Product A and Product B
Appen
-
Ratings
Jupyter Notebook
8.8
19 Ratings
2% above category average
Flexible Model Publishing Options00 Ratings8.819 Ratings
Security, Governance, and Cost Controls00 Ratings8.718 Ratings
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User Ratings
AppenJupyter Notebook
Likelihood to Recommend
10.0
(1 ratings)
8.3
(22 ratings)
Usability
-
(0 ratings)
10.0
(1 ratings)
Support Rating
-
(0 ratings)
9.0
(1 ratings)
User Testimonials
AppenJupyter Notebook
Likelihood to Recommend
Appen
It is well suited for the users and potential employee who are free of any job perspective and need their free time to be utilized. Users can use their free time to be used for submission of interesting tasks.
Whereas the number of tasks are very less and processing time is also very extensive and recruitment takes time more.
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Open Source
I've created a number of daisy chain notebooks for different workflows, and every time, I create my workflows with other users in mind. Jupiter Notebook makes it very easy for me to outline my thought process in as granular a way as I want without using innumerable small. inline comments.
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Pros
Appen
  • Project listing
  • Hiring of the potential and qualified users
  • Tracking of the projects
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Open Source
  • Simple and elegant code writing ability. Easier to understand the code that way.
  • The ability to see the output after each step.
  • The ability to use ton of library functions in Python.
  • Easy-user friendly interface.
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Cons
Appen
  • Selection procedure is bit .
  • The questionnaire need to be reviewed.
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Open Source
  • 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
Appen
No answers on this topic
Open Source
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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Support Rating
Appen
No answers on this topic
Open Source
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
Appen
Appen offers projects mostly related to my native language and also according to my expertise . It offers very interesting projects to be completed , which requires not very expertise and less time to be completed for each task. It is also very convenient to use after selection for the task and also well rewarding against the time consumed for the task completion.
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Open Source
With Jupyter Notebook besides doing data analysis and performing complex visualizations you can also write machine learning algorithms with a long list of libraries that it supports. You can make better predictions, observations etc. with it which can help you achieve better business decisions and save cost to the company. It stacks up better as we know Python is more widely used than R in the industry and can be learnt easily. Unlike PyCharm jupyter notebooks can be used to make documentations and exported in a variety of formats.
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Return on Investment
Appen
  • It has Positive impact as it provides opportunity for new jobs in my area of expertise.
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Open Source
  • 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