G2 reviewers report that Deepnote excels in collaboration features, allowing users to code and work together seamlessly without the need for complex environment setups. This is highlighted by feedback mentioning "online coding and collaboration with colleagues without environment deployment."
Users say that The Jupyter Notebook offers a clean interface that is particularly beneficial for Python and machine learning tasks. Reviewers appreciate features like "the tools for editing each cell and the undo feature," which enhance the overall user experience.
According to verified reviews, Deepnote's integration of an AI Assistant is a standout feature, providing users with helpful suggestions and tools directly within their notebooks. This integration is praised for its seamless functionality, making it easier to utilize various tools effectively.
Reviewers mention that The Jupyter Notebook shines in its ease of use, with many users noting that "receiving the output for each line makes it easier to follow and track every step in the process." This feature is particularly valuable for those who prioritize clarity in their coding workflow.
G2 reviewers highlight that while both platforms have strong support, Deepnote edges out slightly with a higher quality of support rating. Users appreciate the responsiveness and helpfulness of the support team, which can be crucial for troubleshooting and guidance.
Users report that The Jupyter Notebook has a slight advantage in setup ease, with many finding it straightforward to get started. This is complemented by its strong performance in handling Python tasks, making it a reliable choice for users focused on data science and analytics.
Do you have any plans to keep allowing users to save jupyter notebooks without obligating them to use "cloud services"?
1 Comment
TM
I always encourage students to have a local copy. I just wish there was an easier way to run it locally on Win10/Mac. Anaconda makes it simpler but it is...Read more
What is the best way to debug using Jupyter notebook?
1.Code cells for writing and editing code.
2.Markdown cell for writing comments and/or code functions.
3.Raw Jupyter NBConvert cells.
4.A support for...Read more
With over 3 million reviews, we can provide the specific details that help you make an informed software buying decision for your business. Finding the right product is important, let us help.