Notes, Resources and more relating to Data Science
Concepts 🧠 link
- Creating Confidence Intervals for Machine Learning Classifiers link
- The fallacy of placing confidence in confidence intervals link
Newsletters 📃 link
- Data Science Weekly Newsletter link
- Deep (Learning) Focus link
- Shiny Weekly: News from the R Shiny Community link
- Albert Rapp - 3 Minutes Wednesdays link
- Probably Overthinking it - DS, Bayesian Stats and other ideas link
- The Batch - What Matters in AI Right Now link
- This Week in Data Viz link
Blogs/Posts/Articles 📃 link
- TidyverseSkeptic - An opinionated view of the Tidyverse "dialect" of the R language. link
- Resources for learning about the history of statistics and statisticians. link
- R-Tips-and-Tricks - solution to R newbie problems I encountered. Mainly mapping and tidyverse stuff. link
- Sebastian Raschka link
Data Wrangling 🧰 link
- data.table workshop - introduction to, as well as some hands-on experience in using, the data.table package in R. link
- data.table Tutorial - A tutorial on the data.table package link
- A gentle introduction to data.table link
- The ultimate R data.table cheat sheet link
- A data.table and dplyr tour link
- Arun Srinivasan - UseR 2017 dat.table tutorial - link
- Data.Table – everything you need to know to get you started in R link
Learning Resources 🏫 link
- Free data science resources - Thematic list of high-quality data science resources link
- Data Science Learning Resources - A collection of data science and machine learning resources that I've found helpful (I only post what I've read!) link
- Microsoft - Time Series Forecasting Best Practices & Examples link
- Awesome R Learning Resources - collection of free resources to help deepen your understanding of the R programming language. link
- Awesome R - A curated list of awesome R packages and tools link
- Grant McDermott - Data science for economists link
- Richard McElreath - Statistical Rethinking (2022 Edition) link
- ECON 5253: Data Science for Economists link
- Economics 421: Introduction to Econometrics (Winter 2021) link
- Empirical Economics with R link
- Open Source Society University (OSSU) - Path to a free self-taught education in Computer Science! link
- Open Source Society University (OSSU) - Path to a free self-taught education in Data Science! link
- The Open Source Data Science Masters link
- rstats-ed - List of courses teaching R link
- VIP cheatsheets for Stanford's CS 229 Machine Learning link
- A comprehensive 10-page probability cheatsheet that covers a semester's worth of introduction to probability. link
- Data Science Cheatsheet link
- Data Science Cheatsheet 2.0 link
- MLE / DS / SWE Cheatsheet link
- Machine Learning Research & Engineering - Flashcards link
Packages 📦 link
- Google abpackage - An R package for AB testing leveraging pre-period information link
- Google CausalImpact - An R package for causal inference in time series link
- rspivot - Shiny gadget for RStudio for viewing data frames. link
- rpivotTable - A R wrapper for the great library pivottable link
- Awesome Shiny Extensions - R packages that offer extended UI or server components for the R web framework Shiny link
- Awesome R Shiny - An awesome R-shiny list! link
- CalCAT - California COVID Assessment Tool link
- Spotify Habits - Shiny App to visualize and analyse your listening habits link
Books 📚 link
- R Books - A curated list of
rstatsbooks link - Think Bayes - an introduction to Bayesian statistics using computational methods. link
Datasets 📈 link
- ladata - A collection of datasets on Latin America link
- The Economist - multilevel Bayesian model to predict US presidential elections. link
- LA Times - Datadesk - All of our computational notebooks link
- fivethirtyeight - R package of data and code behind the stories and interactives at FiveThirtyEight link
- fivethirtyeight Data - Data and code behind the articles and graphics at FiveThirtyEight link
- Buzzfeed - link
- Jeff Sackmann - Point-by-point data for Grand Slams, 2011-current 🎾 link