Data Science with R and Python- A Round Up: February 2020

We are back with February 2020’s “Data Science with R and Python Round Up”. The new year resolution is that to continue the monthly round up compiling compile interesting news, Python, R blog posts on anything related to learning, data, data science, ML and AI. It just hopes to offer one more chance catch up on the interesting things that was on the twitter/news.

The round up for February has a lots of opportunities for learning.

• Google Summer of Code is a fantastic program enabling students to get into open source software development. As part of the GSoC, students spend three months of the summer working on a programming project. Google Summer of Code has announced the organizations that are part of this year’s program. Are you a student looking for internships, this is a great opportunity. Check here for on the application time line for Google Summer of Code.
• While we are in the topic of internships, RStudio has announced their internship positions for this summer. This is RStudio’s 3rd summer intern program and has 5 openings to work on all things tidy for 10 weeks from May 2020. Two great things about RStudio’s internship program is that the inter does not have to be a student. Everyone can apply and it can be remote as well. Check out here to learn more about RStudio’s internship program and positions.

RStudio has made available the videos of all talks from its conference RStudio 2020. It is a fantastic resource to learn all things Data Science with R and RStudio. Here are a few talks that are a must watch
• Object of type ‘closure’ is not subsettable – Jenny Bryan
• State of the tidyverse – Hadley Wickham
• Not So Standard Deviations Episode 100 – Roger Peng & Hilary Parker (and the only one on video)
• Total Tidy Tuning Techniques – Max Kuhn
• There are a lots more interesting talks at RStudio 2020. Check out the RStudio page for RStudio Conference 2020 videos

MIT’s official introductory course on deep learning methods with applications in medicine and more is available online for free. http://introtodeeplearning.com/

Ever experienced the pain from R’s default option StringAsFactors=TRUE, while creating a dataframe? Pretty soon you have the relief from stringsasfactors pain. Starting with R 4.0.0 release, R will have stringsAsFactors = FALSE by default. Check out R blogpost announcing the news.

Just recently wrote a blog post on 10 Tidyverse Tricks using tweets from David Robinson’s talk. Just found that the actual video of the tidyverse tricks talk available. Check the video

• 12 Steps to Applied AI: A roadmap for every machine learning project, by Cassie Kozyrkov
• A really interesting blogpost by Vicky Boykis on Why don’t we get the news we need?
  Why didn’t the New York Times mention FindFace? Check the mentioned NY Times article on privacy with AI- Clearview AI: The Secretive Company That Might End Privacy as We Know It. A little-known start-up helps law enforcement match photos of unknown people to their online images — and “might lead to a dystopian future or something,” a backer says.
• Check out Allen Downey’s Bite Sized Bayes notebook on Bayes table for Bayes Theorem
• Largest gift in Berkeley’s history will create a ‘hub’ for advancing data science