Deepnote
DeepnoteReviews from AWS customer
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Great tool for those who work or want to work with data science
What do you like best about the product?
The design, the documentation and the community.
What do you dislike about the product?
Nothing really. Ican't remember any negative aspects.
What problems is the product solving and how is that benefiting you?
Helping me with my Machine Learning studies as well as creating my portfolio of Data Science and Machine Learning projects.
Cloud Jupyter Notebook On Steroids
What do you like best about the product?
UI, Cloud, Remote Machine, Collaboration, Integrations, Snowflake, Scheduling, Intellisense, Upgrade Hardware Options
What do you dislike about the product?
Minor Bugs and need to improve the feature for showing a library's documentation (Command + Tab inside a function)
What problems is the product solving and how is that benefiting you?
With Deeepnote being a Cloud Jupyter Notebook on steroids, I am doing things like cleanly pulling data from internal/external sources and pushing it to our databases on a schedule by utilizing many of Deepnote's easy-to-implement features and integrations. Deepnote is the future and a massive improvement over traditional local Anaconda Jupyter Notebooks.
Exciting platform for quick cell based notebook development
What do you like best about the product?
Deepnote allows easy management of new python and other coding environments. It makes available many new strater templates with data so you can have a good baseline. All packages are installed and availble and its easy to see the compute resource being used.
What do you dislike about the product?
Deepnote does not have many options to customize the interdace for users. Fonts and cells make it hard to read sometimes with minimal code editing fnctionality. It should also contain dark mode option for coding friendly environments, as the white background is very glaring on a bigger monitor.
What problems is the product solving and how is that benefiting you?
Deepnote allows easy setup, and fast acccess to a coding environment. It saves work and can be accessed from anywhere. It helps productivity and collaboration because sharing files and adding teammates to projects is seamless.
Recommendations to others considering the product:
Consider it doesn't have dark mode, and how much more flexibility you can achieve with a custom jupyter environment.
My current day-to-day workbench for data science
What do you like best about the product?
Intuitive UI, ease of configuration with lots of integrations, publishing function allows me to present end results directly from Deepnote, concurrent collaboration
What do you dislike about the product?
Because Deepnote is based on the IPython core, not all features from the Jupyter ecosystem are available yet (e.g. ipuwidgets)
What problems is the product solving and how is that benefiting you?
Teaching data science courses, standard data science workbench for clients working in small teams (2 to 5 teammembers). I sue it as my daily front-end to GCP, BigQuery and Prefect.
Recommendations to others considering the product:
Make sure you have a standardized, notebook based workflow with Git. Otherwise this may not fit your bill.
An excellent collaborative python workbook full of features and more!
What do you like best about the product?
I like Deepnote because it is simple to use yet increasingly more and more feature-rich with all the modules one could plugin. The collaboration aspect makes it really cool especially in the remote era. From beginners to pros I believe Deepnote should make your shortlist.
What do you dislike about the product?
There isn't anything I dislike about Deepnote. Maybe when I left an instance running as I stepped away only to forget but that is on me. Deepnote is on point.
What problems is the product solving and how is that benefiting you?
From the beginning, it was easy to use the platform. Saving time, having a location readily accessible and ready for research to production and across a diverse geography. And the collaboration aspect promotes synergy and should help production.
Everything I want in a data science tool
What do you like best about the product?
Deepnote is quick and easy to use. It is robust and reliable. It has totally changed how I do my data analysis. Just open a browser and off I go. Long calculations just get done in the background while I jump in another tab and work on a seperate project.
Love it.
Love it.
What do you dislike about the product?
My only dislike about Deepnote is the lack of dark mode. Had to use a chrome extension to achieve dark mode.
What problems is the product solving and how is that benefiting you?
I don't want to manage a local python environment. Deepnote manages all this for me from the browser.
Additionally, I can easily share projects with colleagues who can access my project and we can both work in the same project at the same time.
Additionally, I can easily share projects with colleagues who can access my project and we can both work in the same project at the same time.
Best data science notebook - by far!
What do you like best about the product?
Great UI, amazing and very responsive support, all our issues had been sorted pretty fast. Also they are conitnuously adding new features, which is really great!
What do you dislike about the product?
Nothing, it's a great product overall, better than all of its competitors
What problems is the product solving and how is that benefiting you?
Different data science tasks, training neural networks
Very efficient notebooks
What do you like best about the product?
Keystroke efficiency combined with hardware availability, also the all-in-one platform style (similar to Pycharm)!
What do you dislike about the product?
I wish there was a bigger community of users.
What problems is the product solving and how is that benefiting you?
Sharing data science work is handy. A lot of the problems I have with Jupyter aren't a problem here and it is MUCH more aesthetically pleasing to use.
Using deepnote for advanced business processes and pipelines
What do you like best about the product?
The flexibility of Deepnote is likely what I like best. We use it for a growing number of business ETL tasks and data pipelines. For advanced Slack messages, like automating our monthly sales progress alerts (with charts and all!). We've used it for heavier tasks like machine learning model training, and so on. It's held up with each task and project and doesn't show any signs of strain. For that, it's become the most important tool in our DataOps team stack.
As well, the community is great. It's active, friendly, and people are always helpful.
As well, the community is great. It's active, friendly, and people are always helpful.
What do you dislike about the product?
If I had to choose something, it'd be the lack of things like ipywidgets. The ability to make notebooks more interactive is nice to help out less tech-savvy team members who'd rather use drop-downs and buttons over coding themselves.
What problems is the product solving and how is that benefiting you?
The main problem Deepnote has solved is bringing our various data processes under one roof. In the past, we had code running locally, in spots like Zapier, hosted on AWS, and so on. Our main goal was to condense and slim down our DataOps stack and Deepnote has been the key player in doing that. Data processes including ETL, alerts, machine learning, etc.
The most significant benefit we've realized is the collaborative ability of the notebooks and the ability to add in comments, notes, etc., to help explain things for team members who don't necessarily understand the code.
Additionally, it's sped up our testing and staging immensely. Deepnote feels more-or-less like developing locally on your computer, but since it's in the cloud and hosted, it's typically a step closer to being demoed and "shown off" than it would be if it were just local. With recent web tunneling updates, this has been enhanced even more so.
The most significant benefit we've realized is the collaborative ability of the notebooks and the ability to add in comments, notes, etc., to help explain things for team members who don't necessarily understand the code.
Additionally, it's sped up our testing and staging immensely. Deepnote feels more-or-less like developing locally on your computer, but since it's in the cloud and hosted, it's typically a step closer to being demoed and "shown off" than it would be if it were just local. With recent web tunneling updates, this has been enhanced even more so.
Great tool to foster open, collaborative, and reproducible research and teaching
What do you like best about the product?
Easy to use and convenient integration with Docker and Github.
What do you dislike about the product?
Compared to Python, relatively few R packages are installed by default. But once I connect it to a Docker container, I can use all of my favorite R packages.
What problems is the product solving and how is that benefiting you?
Foster open, collaborative, and reproducible research, teaching, and learning.
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