Deepnote is an AI tool designed to assist data scientists and analysts by providing AI-powered code suggestions within their notebooks. It aims to enhance productivity and efficiency by offering contextualized and lightning-fast coding suggestions, thereby reducing the need for repetitive and boilerplate code writing. The tool can understand and generate relevant code suggestions based on the context provided by the user and does not require additional applications or tools for integration. Deepnote stands out for its dynamic and versatile nature, offering an immersive workspace with collaborative features that foster big-picture focus and enhance productivity for analytics professionals. It excels in providing deep context-awareness, an extensive context repository, and is actively working on introducing conversational AI features for SQL in addition to code suggestions.
Deepnote Copilot was created by a team at Deepnote. The platform was launched on June 20, 2023. Deepnote is a company focused on providing a dynamic and versatile platform for data scientists, analysts, and programmers, with features such as Python and other languages support, contextualized code suggestions, immersive workspaces, and collaborative notebooks.
To use Deepnote Copilot, follow these steps:
Paid plans start at $31/month and include:
I appreciate the AI-powered code suggestions that save me time when writing repetitive code. It's particularly helpful for data analysis tasks.
The interface can be a bit overwhelming at first, and sometimes the suggestions are not as contextual as I'd like.
Deepnote helps me reduce the time spent on coding by providing relevant suggestions, but I still find myself needing to make manual adjustments often.
I love the collaborative features, which make it easy to work on projects with my team in real time. The AI suggestions are quite helpful too.
I wish there were more tutorials to help new users get started with the tool effectively.
It streamlines the coding process for data science projects, allowing me to focus on analysis rather than boilerplate code.
The code suggestions are usually accurate and save me a lot of time when I'm working on data projects.
Sometimes, the AI doesn't understand the context perfectly, leading to irrelevant code suggestions.
It helps me code faster and with fewer errors, making my data science workflow much smoother and more efficient.