BestLinks, R

Best links of the week #15

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Best links of the week from 15th April to 21st April


  1. When it comes to clustering, depending on the algorithm used, one may have a hard time determining the appropriate k (number of clusters). Some algorithms do not require it, but for the ones that do, such as k-means, you should have a look at the elbow method to evaluate the appropriate k or at the silhouette of objects regarding the clusters.
  2. Dunder Data is a professional training company dedicated to teaching data science and machine learning. There is paid and free online material.
  3. Software Carpentry, teaching basic lab skills for research computing.
  4. ROpenSci, transforming science through open data and software.
  5. mlmaisleve, conceitos rápidos e leves sobre Machine Learning ?.
  6. kite, Code Faster in Python with Line-of-Code Completions.


  1. Correlation does not even imply correlation (tricky, but worth a read) at Andrew Gelman’s Blog.
  2. Why are (almost all) economists unaware of Milton Friedman’s thermostat? at Worthwhile Canadian Initiative.
  3. Comments about above link here at The Monkey Cage.
  4. Summer Short Course “An Introduction to Causal Inference” at Causal Analysis in Theory and Practice.
  5. The Master Algorithm at Data Skeptic.
  6. The 5 Basic Statistics Concepts Data Scientists Need to Know by George Seif at Towards Data Science.
  7. The 5 Clustering Algorithms Data Scientists Need to Know by George Seif at Towards Data Science.
  8. Into the world of clustering algorithms: k-means, k-modes and k-prototypes by Alessia Saggio at AMVA4NewPhysics.
  9. K-modes at The Shape of Data.
  10. Hierarchical clustering with mixed type data – what distance/similarity to use? at Cross Validated.
  11. It’s Okay to Break the Rules, Sometimes by Ken Flerlage at Data Visualization Society.
  12. How Pew Research Center uses small multiple charts by Peter Bell at Decoded / Pew Research Center.
  13. How do we know when a visualization is good? Perspectives from a cognitive scientist by Lace Padilla at Multiple Views – Visualization Research Explained.
  14. Análise das Vítimas de Acidentes de Trânsito nas Rodovias Brasileiras – Parte 2 at Gabriel Lima Goes LinkedIn Profile.


  1. Algoritmos Genéticos – Aplicação no R at EstaTiDados YouTube Channel.

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