Best links of the week #4

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Best links of the week from 28th January to 3rd February.

Links

  1. Upload your CV and get suggestions and corrections at CV Compiler.
  2. Regression toward the mean at Wikipedia.
  3. Free and open resource with Machine Learning papers, code and evaluation tables at Papers With Code.
  4. Machine Learning Timeline at Leandro Mineti’s GitHub.
  5. Vários algoritmos de Machine Learning at Arnaldo Guaberto’s GitHub.
  6. AN AI READING LIST — FROM PRACTICAL PRIMERS TO SCI-FI SHORT STORIES at The Verge.
  7. Como camuflar seu WhatsApp Web usando Snippets JavaScript at VivaOLinux.
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Best links of the week #3

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Best links of the week from 21th January to 27th January.

Links

  1. The bioinformatics chat is a podcast about computational biology, bioinformatics, and next generation sequencing.
  2. Trilha de estudos de Data Science at fcqueiroz’s GitHub.
  3. Jonas Salk: Good at Virology, Bad at Economics at Slate.
  4. Why is Data Preprocessing required? at Ques10.
  5. What bioRxiv’s first 30,000 preprints reveal about biologists at Nature.
  6. What are some recent examples of Simpson’s Paradox in the media? at Quora.
  7. More funny examples of correlations at Bloomberg.
  8. If correlation doesn’t imply causation, then what does? at Data-Driven Intelligence.
  9. Berkson’s Paradox at Brilliant.
  10. Causal Inference & Paradoxes at IRT SystemX.
  11. 10 Biggest Struggles of PhD Students at INOMICS.
  12. Interesting Correlation does not imply causation article at Wikipedia.
  13. If two variables are independent, they will also be linearly independent, therefore their pearson product-moment correlation coefficient (or aka correlation) will be 0. However, the converse is not necessarily true, for they can be linearly independent but non-linearly dependent. However, it is sometimes mistakenly thought that linearly independence does imply independence when the two random variables are normally distributed. This is false though, because normally distributed and uncorrelated does not imply independent at Wikipedia.
  14. What is a Monotonic Relationship? at Statistics How To.
  15. One-Tailed and Two-Tailed Hypothesis Tests Explained at Statistics by Jim.
  16. What are the differences between one-tailed and two-tailed tests? (and many more interesting statistics questions here) at Institute for Digital Research and Education.
  17. Probability Tutorials at Probability.NET
  18. Google DataSet Search
  19. What Is An Intuitive Way To Understand Entropy? at Forbes.
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Best links of the week #2

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Best links of the week from 14th January to 20th January.

Links

  1. Data Hackers BR is apparently the largest community for Data Science in Brazil. They own a blog, a podcast, a Slack channel and a mailing list.
  2. Peeriodicals is a platform where you can compile a set of [existing] articles into a virtual journal, becoming its Editor-in-chief. People can subscribe to your jornal and follow your editions, just like they would in a real journal.
  3. Alerta máximo contra as pseudociências at Unicamp Notícias.
  4. TLM is a new open-source project that aims to create an interactive textbook containing A-Z explanations of concepts and methods, algorithms and their code implementations from the fields of data science, machine learning, deep learning, natural language processing, statistics, and more. TLM also seeks to link these fields to each other, highlighting their correlation.
  5. Cookiecutter Data Science: A logical, reasonably standardized, but flexible project structure for doing and sharing data science work.
  6. Faster Data Science Education at Kaggle.
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Best links of the week #1