Deepnote
Collaborative computational notebook that can help you and your team to analyze data, train models or simply work together on some Python code.
How can Deepnote help us?
At Robothon, Deepnote can be particularly useful for teams working on data science or AI projects, since you will be able to immediately create a full featured computational environment, so you save time on setup. Out of the box, you will get:
- Python notebook to do interactive analysis (compatible with Jupyter)
- Data science environment with all the common tooling pre-installed
- Full access (including root) to the underlying machine - add whichever libraries you want
- Collaboration - share your project like you are used from eg. Google Docs
- Data visualisations and rich previews for common libraries (eg. pandas)
- Publishing - you can publish nice articles or reports from your notebooks
- Github integration
Check out our example projects in Python, showcasing Pandas, Keras, and visualisation possibilities.
How to use it?
Simply head over to https://deepnote.com/, hit Sign up and go. The in app onboarding might help you to the first steps, but if you know Jupyter, you will immediately feel at home.
Mentors
Two guys from Deepnote joined Robothon to help you with your projects.
Jan Matas
Jan is the CTO of Deepnote and a massive fan of robotics and AI. He published research on Reinforcment learning for robotics using simulations to teach neural nets how to operate real robots in various manipulations tasks. Before joining Deepnote, he worked at Google, Palantir or Two sigma investments. Jan will be happy to help with:
- Anything to do with physical robots - electronics, controllers (Arduino, Raspi, Atmel etc.), programming, robotic algorithms (particle filters, PID controlers, kalman...)
- Reinforcment learning and more generally ML (pointing you to the methods to try)
- System design and architecture - advice on how to quickly build app/webapp
Jakub Zitny
Jakub is a software engineer at Deepnote and also an ML researcher at FIT CVUT interesred in medical imaging and ML explainability. Before joining Deepnote, Jakub worked at Avocode and also organized multiple editions of HackPrague. He would be happy to help with:
- General machine learning questions
- How to build a great webapp for your idea
- System design and architecture - advice on how to quickly build app/webapp
- Questions related to healthcare data and IT-related regulations
