We're here with another Community roundup, spotlighting the top notebooks and community contributors of March 2021.

As always, if you're tagged in this post and would like to get some snazzy Deepnote swag for your hard work, please DM  Elizabeth Dlha  with your full name, T-shirt size and address. Also, the Deepnote publishing competition is still on - don't forget to share your notebooks in the Showcase channel to win $1,000 and other prizes. Now back to the business 👇

⚽  Dan St Paul  built an EPL webscrapper in Deepnote to get some quality soccer data using pandas and Watir/Nerodia as an alternative to Selenium.

🌊 Ferdie Taruc did an awesome sentiment analysis on Frank Ocean's lyrics - he walks through everything from data gathering, clearing, to the sentiment analysis itself and statistical testing.

🐦  Abid  trained a machine learning model to predict sentiment from tweets in Arabizi Dialect. It nicely shows how you can use ML to better understand and interpret content.

👨‍🎓  Reslan Tinawi  showcased different exploratory data techniques on a data set with graduate admissions data. The goal is to predict the student's chance of admission to postgrad, given different predictor variables.

📻  Jacob Lower  and  Allan Campopiano  built a notebook utilizing YouTube API to get some channel data and visualize data about the popular YouTube channel Good Mythical Morning.

🐊  Tejas Jain  weorked with COVID-19 news data from IEEE to build a text summarization NLP model.

🤖  Andrej Chudy  built a Telegram bot to receive model training updates from Deepnote. Check out the notebook to replicate his approach and get one for yourself!

💸 birlorg created a notebook guiding us on how to retire in about 15 years.

🔮 Lukas Frei did a research piece analysing behavior of the data science community during the covid. You can read the full article here and see the supporting code in his notebook.

🕵️ Basile Roth built a social distancing detector using a Tensorflow object detection model, Python and OpenCV.

Community MVPs

🚀 Top post starter:  Abid  

👑 Most appreciated member:  Elena Semeyko  

💬 Most active commenter:  Franccesco Orozco  

Hi community, I've recently found out that ecology/biology students are learning NCAR Command Language (NCL) for visualizing some of their datasets. I hear that setting up NCL, conda, X11 and everything might be pretty complicated so I went ahead and created a NCL notebook in Deepnote.

It's not really a complete custom env, there are some problems with installing, but feel free to duplicate my project and do whatever you need. Modifications, and feedback is welcome!

Here it is: https://deepnote.com/project/bf2ffd09-c9e8-4d3b-8516-e8af1f4f62c6#%2Fnotebook.ipynb

I engineer things at Deepnote, right now I am trying to get our community to grow 🙌🏻

We just refreshed our publishing feature, and are about to roll out public profiles — so you can showcase your projects similarly as on GitHub, yayy.

Over the weekends I'm trying to finish my PhD in Applied Deep Learning in Medical Imaging. Previously I worked for Avocode. 

Dynamic Website Scraper built in Deepnote by the one and only Daniel St Paul. See project in Deepnote here.