The third post in my #MovingPastTutorials series is out! This time, I wrote about pseudocode!
If you are staring at a blank text editor unsure where to start, this one's for you!
dev.to/aspittel/moving-past-…
I took some time this morning to pull together all my #rstats tutorials on Kaggle! I've got stuff for everybody from non-programmers to people looking for NLP resources.
Hope y'all find them helpful! 🤓📚💻
kaggle.com/rtatman/rachael-s…
I just taught a 2 days course on #dataviz with #rstat. I share the course material in case it can help somebody:
yan-holtz.com/teaching
Included: DataViz intro & caveats, ggplot2, R Markdown, and Github intro
I'm seriously considering turning my "Data Science for Economists" course notes into a book. github.com/uo-ec607/lectures
You can help me decide by answering three simple polling questions below!
(Comments and retweets appreciated.)
I have a big announcement! 🎉
New programmers tend to struggle with putting together the pieces of the puzzle when creating bigger projects.
So, I'm creating a multimedia series on problem solving, breaking down problems, debugging and more.
dev.to/aspittel/moving-past-…
In our latest post, our Robust & Verified AI team introduces our work on rigorous specification-testing (catching bugs), robust training (eliminating bugs) and formal verification (proving the absence of bugs) of ML models.
deepmind.com/blog/robust-and…@pushmeet DJ @uesatoj @sgowal
I've made this cheat sheet and I think it's important. Most stats 101 tests are simple linear models - including "non-parametric" tests. It's so simple we should only teach regression. Avoid confusing students with a zoo of named tests. lindeloev.github.io/tests-as… 1/n
I'm going to attempt to crack a password in a SQL database to help fight crime in this video. In order to do so, we'll have to learn about the fundamental topics in Discrete Math (combinatorics, graph theory, set theory, number theory, logic, & recursion) youtu.be/LGt4PE7-ATI
🐦 Wanna use twitter data like a pro? (slides & code)
📽 "rtweet workshop: Collecting and analyzing Twitter data" by @kearneymw
buff.ly/2B3H9hn#rstats#ddj
ALT rtweet-workshop Collecting and analyzing Twitter data by Michael W. Kearney School of Journalism Informatics Institute University of Missouri @kearneymw
My PhD thesis Neural Transfer Learning for Natural Language Processing is now online. It includes a general review of transfer learning in NLP as well as new material that I hope will be useful to some.
ruder.io/thesis/
✋ ‘If you use statistics in research, business, or policymaking but are not a statistician, these articles were indeed written with YOU in mind.’
📄 Moving to a World Beyond “p < 0.05” — @Ron_Wasserstein et al.
buff.ly/2ukJr7H#statistics
Want to understand #Python exceptions? I highly recommend this post by @ConquerProgram1: conquerprogramming.com/blog/…
New to exceptions? You'll learn how & why to use try/except/else/finally
Already using exceptions? You'll learn how to use exceptions to write more Pythonic code 🐍
Here's another example from the workshop I am presenting next week: using Python to count word frequencies, bi-grams, and tri-grams, then generate a random Grimms' fairy tale:
nbviewer.jupyter.org/gist/Al…
In this week's #tidytuesday screencast, I analyze data on board games🎲♟️
This includes fitting a lasso regression model to predict a game's rating, using glmnet, broom, and other #tidyverse packages. Some fun feature engineering and model exploration! youtube.com/watch?v=qirKGdQv…