Every week we analyze the most discussed topics on Twitter by Data Science influencers
The following topics, URLs, resources and tweets have been automatically selected by a custom topic extraction model. Want to know more? Jump at the end of this article!
This Week Overview
This week, Data Science influencers talked about:
- New Releases in R: spatialsample, parsnip, knitr…
- Innovative AI Applications
- A Reddit-fueled spike in GameStop Shares
Here are all the details for each topic:
New Releases in R: spatialsample, parsnip, knitr…
This week, influencers shared updates on new releases of R packages.
Julia Silge shared the release of spatialsample, a new tidymodels package for resampling spatial data. The goal of spatialsample is to provide functions and classes for spatial resampling to use with rsample, including Spatial clustering cross-validation.
Emily Robinson retweeted about the new release of parsnip, a tidyverse package that standardizes the interface for fitting models as well as the return values. It now also includes an RStudio IDE add-in that helps make model specifications super easy.
Mara Averick retweeted about the release of an additional feature on knitr R package that facilitates adding alt-text to images inR Markdown-produced documents.
Innovative AI Applications
Data Scientist influencers shared different innovative applications of artificial intelligence.
Jean-Baptiste Lefevre shared a video showcasing a very promising AI project developed by Abhishek Singh. This Tensorflow-based project combines computer vision with speech recognition to enhance Alexa’s capabilities to allow it to understand sign language using computer vision. So, people using sign language could easily interact with virtual AI assistants like Alexa, Google Home or Apple HomePod, etc.
He also shared a video showing a robotic arm with embedded computer vision in action in the domain of logistics. The KUKA KR Delta and KUKA PickControl are industrial robots using conveyor tracking with integrated image processing to easily coordinate and control multiple robots for the fast-moving consumer goods (FMCG) market segment.
Another illustration of AI application was given by Shi that shared an article on how teams of scientists equipped with machine learning algorithms, intelligent sensors and greenhouse automation beat traditional farmers in a strawberry-growing contest, a Smart Agriculture Competition that took place in China.
Reddit-fueled spike in GameStop Shares
Last week Redittors from r/wallstreetbets decided to teach a lesson to Wall Street Big Shots. They’ve been buying up shares in struggling video game store GameStop and causing chaos on the stock market.
Peter Wang shared a thread explaining how GameStop (GME) isn’t a stock anymore but rather a “fulcrum, testing the collective resolve of pissed-off Main St vs Wall St”. Randy Olson also tried to summarize what’s going on with GameStop in 4 charts:
Influencers reacted to a series of tweets from Mat Velloso wondering how long will it take until GameStop is turned into a crypto currency. While Drew Fustin reacted to another interesting question from Lee Edwards asking Twitter what they would do if they were on GameStop’s board right now?
Finally, Randy Olson, illustrated the feelings of “watching /r/wallstreetbets dudes become millionaires overnight with #GameStop stock while his index funds went down today” by this gif:
In order to find Twitter most discussed topics within the data science community, we created a whole pipeline combining influencers analysis, data extraction and NLP using the BERTopic Python library, a topic modeling technique that leverages:
- Sentence Transformers, to obtain a robust semantic representation of the texts
- HDBSCAN, to create dense and relevant clusters
- Class-based TF-IDF (c-TF-IDF), to allow easy interpretable topics whilst keeping important words in the topics descriptions.