Deepnote
DeepnoteReviews from AWS customer
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Well Organized Notebook and Code Space that Efficiently Blasts Through Visualization and Latex Work
What do you like best about the product?
The most helpful: The embedded Chat GPT AI enables me to move extremely quickly to do complex visualizations across meshgrids, quickly turn collected data into data frames, and after providing clear examples of the backend code or functions I would like to run, is able to permute or iron out my work. Basically Deepnote lets me work really quickly, given I know what I'm trying, and then share the results cleanly. Saves me so much time.
What do you dislike about the product?
It used to be that the AI generation window would cover error messages. I believe that's been improved. In addition it used to be that as you typed text it would always try to autocomplete, which would be distracting for non code text. That has also been made optional.
Right now it's that the performance for long notebooks ("Deep Notebooks") can get really bad, especially on Chrome on Linux. It can get to the point where I can't open some of my notebooks in Chrome because they will just crash the browser.
Also, I would like the table of contents feature to be an optional hover window so I can see it anywhere. For DeepNotes with lots of variables, having to scroll through all the variables to get to the table of contents defeats the purpose of the table of contents in the first place.
Right now it's that the performance for long notebooks ("Deep Notebooks") can get really bad, especially on Chrome on Linux. It can get to the point where I can't open some of my notebooks in Chrome because they will just crash the browser.
Also, I would like the table of contents feature to be an optional hover window so I can see it anywhere. For DeepNotes with lots of variables, having to scroll through all the variables to get to the table of contents defeats the purpose of the table of contents in the first place.
What problems is the product solving and how is that benefiting you?
I use Deepnote for many different problems. 1) Performing visualizations, analysis, and developing models or conclusions. Typically I import data into dataframes and then use that data to perform engineering calculations or train models. I then do visualizations of my results. A common case I use it for is optimization for controls and design synthesis problems. I then mix my work with headers and Markdown for organization, and then share my notebooks as Apps.
Deepnote mostly handles all of the very tedious time consuming steps (Data wrangling and plotting) via its ChatGPT integration. Chat GPT is not currently trustable for my mission critical backend optimization or modelling code, but once I have written backend functions, it is able to use those examples, and Deepnote then is able to help me quickly refine and visualize until I get my desired results.
Deepnote mostly handles all of the very tedious time consuming steps (Data wrangling and plotting) via its ChatGPT integration. Chat GPT is not currently trustable for my mission critical backend optimization or modelling code, but once I have written backend functions, it is able to use those examples, and Deepnote then is able to help me quickly refine and visualize until I get my desired results.
The Best Collaborative Data Science Platform Out There!
What do you like best about the product?
Deepnote has completely transformed my workflow as a data scientist. It combines the functionality of traditional Jupyter notebooks with powerful collaborative features, making it an essential tool for any data science team. The platform is incredibly intuitive, with a clean interface and built-in support for all major data science libraries.
One of the standout features is real-time collaboration – I can work alongside my teammates just like in Google Docs, which has significantly boosted our productivity. Setting up projects is seamless, and Deepnote handles the back-end configurations, so we can focus entirely on data exploration and analysis.
The integration with various data sources, from databases to APIs, is smooth and easy to manage, saving us so much time on setup. The support team is also highly responsive and genuinely cares about user feedback, frequently rolling out updates that make the platform even better.
Whether you’re a beginner or a seasoned data professional, Deepnote will elevate your projects. Highly recommend it to anyone looking for a reliable, efficient, and collaborative data science environment!
One of the standout features is real-time collaboration – I can work alongside my teammates just like in Google Docs, which has significantly boosted our productivity. Setting up projects is seamless, and Deepnote handles the back-end configurations, so we can focus entirely on data exploration and analysis.
The integration with various data sources, from databases to APIs, is smooth and easy to manage, saving us so much time on setup. The support team is also highly responsive and genuinely cares about user feedback, frequently rolling out updates that make the platform even better.
Whether you’re a beginner or a seasoned data professional, Deepnote will elevate your projects. Highly recommend it to anyone looking for a reliable, efficient, and collaborative data science environment!
What do you dislike about the product?
Honestly, there’s very little to dislike about Deepnote! If I had to pick something, it would be great to see even more customization options for themes and layout preferences. But even as it stands, Deepnote’s design and functionality are top-notch.
What problems is the product solving and how is that benefiting you?
Real-Time Collaboration,Seamless Integration, Enhanced Code Management, AI-Powered Assistance
Intuitive Collaboration for Data Projects
What do you like best about the product?
Deepnote offers an incredibly intuitive platform for collaborative data analysis, making it easy to share projects and insights with team members. The real-time collaboration feature is particularly useful, allowing multiple users to work on a notebook simultaneously without issues. The integration capabilities with tools like SQL, Python, and data visualization libraries make it versatile for various data needs, from exploration to presentation. The interface is also very user-friendly, which lowers the learning curve for new users, whether they're analysts or product managers."
What do you dislike about the product?
While Deepnote excels in collaboration, there are a few areas that could be improved. The platform can occasionally be slow when handling very large datasets, which impacts productivity. Additionally, while it integrates well with many data sources, it would be beneficial to have more customization options in the data visualization aspects, as the current capabilities can feel limited for advanced visualizations. Lastly, the cost for enterprise features can be a bit steep, which might be a barrier for smaller teams.
What problems is the product solving and how is that benefiting you?
Deepnote is solving several key problems for our data-driven projects, primarily by enhancing collaboration, simplifying data access, and reducing technical barriers. In a typical data analysis workflow, sharing insights and working in real-time with teammates can be cumbersome, especially when using traditional tools. Deepnote's collaborative environment allows multiple users to seamlessly work together in a single notebook, eliminating version control issues and making it easy to get feedback instantly.
Another major benefit is its integration with various data sources and tools (SQL databases, APIs, and cloud storage), which streamlines data access and reduces the time spent on data preparation. This enables us to focus more on analysis and insights rather than data wrangling. For me, as a Product Manager, it’s invaluable to have a platform where I can quickly access up-to-date information and collaborate with analysts on reporting and visualization, which ultimately speeds up decision-making and helps deliver better insights to stakeholders.
Another major benefit is its integration with various data sources and tools (SQL databases, APIs, and cloud storage), which streamlines data access and reduces the time spent on data preparation. This enables us to focus more on analysis and insights rather than data wrangling. For me, as a Product Manager, it’s invaluable to have a platform where I can quickly access up-to-date information and collaborate with analysts on reporting and visualization, which ultimately speeds up decision-making and helps deliver better insights to stakeholders.
Perfect for collaborative projects and creating apps
What do you like best about the product?
The support is very responsive and helpful
What do you dislike about the product?
Sometimes the AI will not correctly fix an issue in the code it will just catch the error and continue rather than providing a solution
What problems is the product solving and how is that benefiting you?
It allows the non technical employees to run projects as an app without the help of a developer
Value for money - Python IDE Cloud based solution
What do you like best about the product?
This cloud-based Python IDE has revolutionized my coding experience.
It's incredibly user-friendly, with a clean interface and intuitive features. The seamless integration with databases and local files with performace has made my model training experience amazing. And it saves me valuable time while collabrating with my team at the development period.
Also, the built-in terminal in this cloud IDE is a lifesaver. I can execute shell commands directly within the IDE, making it a one-stop solution for all my development needs
It's incredibly user-friendly, with a clean interface and intuitive features. The seamless integration with databases and local files with performace has made my model training experience amazing. And it saves me valuable time while collabrating with my team at the development period.
Also, the built-in terminal in this cloud IDE is a lifesaver. I can execute shell commands directly within the IDE, making it a one-stop solution for all my development needs
What do you dislike about the product?
More comprehensive scheduling options and interactive based options could complete the loop with story telling is clean and self servicable.
What problems is the product solving and how is that benefiting you?
It helps in executing huge data set feature extraction and model training. Team can monitor the performance and collabrate at the same place.
Fantastic Tool
What do you like best about the product?
I love how easy Deepnote makes it to work with my team in real-time and create visualizations right in the notebook. Plus, the ability to publish interactive web apps for others is a game-changer—it’s perfect for sharing results in a more engaging way! The AI-powered assistance is also super helpful, catching mistakes and speeding up my workflow. And with smooth integrations for databases and tools like Google Sheets, everything just flows.
What do you dislike about the product?
The only feature I feel is missing is the ability to sync code directly with GitHub or GitLab and deploy via Git. It would be a big help for version control and deployment. Other than that, Deepnote has everything I need for collaborative data science!
What problems is the product solving and how is that benefiting you?
Easily create interactive applications that we can publish with ease—it's almost no-code.
Great Tool for SQL and Python Coding, But Needs Improvements in Library Management and Bug Fixing
What do you like best about the product?
Increased Speed: Writing SQL and Python has become 20x faster for me thanks to Deepnote. I can focus on analysis rather than getting bogged down in coding syntax.
Intelligent Code Assistance: Deepnote understands syntax and functions that I might not be aware of, making coding feel more intuitive. I rarely write SQL or Python code from scratch anymore.
Library Identification: The platform efficiently identifies the necessary libraries for my projects, saving me time and reducing errors.
Human Language to Code Translation: I’m impressed by its ability to translate human language into code with sophistication, making it accessible for users of varying coding expertise.
Intelligent Code Assistance: Deepnote understands syntax and functions that I might not be aware of, making coding feel more intuitive. I rarely write SQL or Python code from scratch anymore.
Library Identification: The platform efficiently identifies the necessary libraries for my projects, saving me time and reducing errors.
Human Language to Code Translation: I’m impressed by its ability to translate human language into code with sophistication, making it accessible for users of varying coding expertise.
What do you dislike about the product?
SQL Variants Recognition: Sometimes, Deepnote struggles to recognize the different variants of SQL depending on the specific database provider, leading to compatibility issues with certain functions.
Import Library Management: The automatic generation of import statements can be problematic, as it sometimes puts imports inline. This can cause issues since we shouldn’t re-import libraries every time we run code. It would be helpful if Deepnote provided a way to manage library imports as a starting command for each session.
AI Bug Fixing Reliability: The AI assistance for bug fixing isn't always reliable, and I often find myself fixing bugs manually, which can be time-consuming.
Import Library Management: The automatic generation of import statements can be problematic, as it sometimes puts imports inline. This can cause issues since we shouldn’t re-import libraries every time we run code. It would be helpful if Deepnote provided a way to manage library imports as a starting command for each session.
AI Bug Fixing Reliability: The AI assistance for bug fixing isn't always reliable, and I often find myself fixing bugs manually, which can be time-consuming.
What problems is the product solving and how is that benefiting you?
Deepnote is solving several key problems in my data analysis workflow. Firstly, it allows me to quickly perform analyses without the need to think about the initial SQL or Python commands, which significantly speeds up my process. About 90% of the time, the code that Deepnote generates is good enough for my needs, enabling me to focus on analyzing the data rather than getting bogged down in coding specifics.
When the auto-generated code isn’t exactly what I want, I can easily refine it due to my background in SQL and Python.
When the auto-generated code isn’t exactly what I want, I can easily refine it due to my background in SQL and Python.
Deepnote has become our go-to for prototyping
What do you like best about the product?
Deepnote's easy to use notebook interface powered by it's cloud-based compute has been a gamechanger for our team. We haven't had to deploy some of our core algorithms to GCP / AWS to do small prototypes, using Deepnote instead. We've even gone as far as building basic prototype apps and embeds using Deepnote. All of this supporting us towards building a functioning MVP.
What do you dislike about the product?
The file management system can be really frustrating. We have been uploading and creating datasets inside of Deepnote, and often accessing the data and moving files into different areas via the interface feels clunky. I end up using terminal because it's a little more seamless, but would prefer a more responsive interface.
What problems is the product solving and how is that benefiting you?
It's helping us prototype using bespoke algorithms we have built without having to mount these to our server environment.
Deepnote makes me feel like I have superpowers
What do you like best about the product?
I love how it works where ever I am - no matter what physical machine I am on at the time.
I love the AI - it helps me so much with code, allowing me to focus on great questions.
It is simple to set up, run and maintain. I switch on an work - simple as that!
I love the interface and workspace - as a self taught data person (50yrs old) I find it allows me to focus on the data and not the IDE.
I love the AI - it helps me so much with code, allowing me to focus on great questions.
It is simple to set up, run and maintain. I switch on an work - simple as that!
I love the interface and workspace - as a self taught data person (50yrs old) I find it allows me to focus on the data and not the IDE.
What do you dislike about the product?
Where are downsides? Well ok...if I have to find some then maybe because it is cloud based some of my future clients might be concened about privacy but I feel you have that covered.
What problems is the product solving and how is that benefiting you?
Deepnotes let me tackle data problems I would have considered above my wirght category. I am new and self taught and Deepnore maks me feel like we can teach old dogs new tricks.
Deepnote: Making collaboration easy
What do you like best about the product?
Deepnote makes collaboration easy and seamless! As a product manager it is the best tool in the market to collaboarte with data team to gather quantitative insights around any version release. It also provides super awesome visualizations that could be downloaded instantly as png. For the past year, i've been using it daily to ehance the productivity of the team.
What do you dislike about the product?
You experience delays on lower plans. On mobile devices the zoom feature on graphs is slightly buggy.
What problems is the product solving and how is that benefiting you?
It helps us in doing compartive data analysis for the new version releases. It also has improved our efficiency as collaboartion between team members oon deepnote is seamless. Most importantly, it's a cost effecient alternative for our data analytics needs.
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