{"id":2885,"date":"2020-02-25T00:12:58","date_gmt":"2020-02-25T00:12:58","guid":{"rendered":"https:\/\/mribeirodantas.xyz\/blog\/?p=2885"},"modified":"2020-02-25T00:13:02","modified_gmt":"2020-02-25T00:13:02","slug":"best-links-of-the-week-57","status":"publish","type":"post","link":"https:\/\/mribeirodantas.xyz\/blog\/index.php\/2020\/02\/25\/best-links-of-the-week-57\/","title":{"rendered":"Best links of the week #57"},"content":{"rendered":"Reading time: <\/span> 2<\/span> minutes<\/b><\/span><\/span>\n

Best links of the week from 17th February to 23rd February<\/h3>\n\n\n\n
\"This<\/figure>\n\n\n\n

Links<\/h4>\n\n\n\n
  1. Luna. A WYSIWYG language for data processing<\/a>.<\/li>
  2. 40 powerful concepts for understanding the world<\/a> at Gurwinder Bhogal’s Twitter<\/a>.<\/li>
  3. Mathematics for Machine Learning (Book)<\/a>.<\/li>
  4. Fairness and machine learning (Book)<\/a>.<\/li>
  5. Mathematicians propose new way of using neural networks to work with noisy, high-dimensional data<\/a> at Phys.org<\/a>.<\/li>
  6. Neuroscience opens the black box of artificial intelligence<\/a> at TechXplore<\/a>.<\/li>
  7. What are the differences between Factor Analysis and Principal Component Analysis?<\/a> at Stack Exchange<\/a>.<\/li>
  8. How does Factor Analysis explain the covariance while PCA explains the variance?<\/a> at Stack Exchange<\/a>.<\/li>
  9. Overview of Lord’s, Simpson’s and Birth Weight paradox<\/a> at Michael Clark’s website<\/a>.<\/li>
  10. Em decis\u00e3o in\u00e9dita ANVISA libera terapias alterantivas no Brasil<\/a>.<\/li>
  11. \u201cS\u00edndrome do sobrinho\u201d na divulga\u00e7\u00e3o cient\u00edfica<\/a> at Revista Quest\u00e3o de Ci\u00eancia<\/a>.<\/li><\/ol>\n\n\n\n\n\n\n\n

    Blog posts<\/h4>\n\n\n\n
    1. Causal Impact: state-space models in settings where a randomized experiment is unavailable<\/a> at Gustavo Millen’s Blog<\/a>.<\/li>
    2. Uber M3 is a Time-Series Database for Massively Scalable Machine Learning Problems<\/a> by Jesus Rodriguez<\/a> at Towards Data Science<\/a>.<\/li>
    3. Probabilistic Model Selection with AIC, BIC, and MDL<\/a> by Jason Browniee<\/a> at Machine Learning Mastery<\/a>.<\/li>
    4. A Gentle Introduction to Model Selection for Machine Learning<\/a> by Jason Browniee<\/a> at Machine Learning Mastery<\/a>.<\/li><\/ol>\n\n\n\n

      Positions available<\/h4>\n\n\n\n
      1. Cientista de dados<\/a> at Ktech!.<\/li>
      2. Est\u00e1gio em An\u00e1lise de Dados<\/a> at UP.<\/li>
      3. Analista de BI [Pleno]<\/a> at DataSprints.<\/li>
      4. Engenharia de Dados [Pleno\/S\u00eanior]<\/a> at DataSprints.<\/li>
      5. Engenheiro DevOps\/SRE<\/a> at iClinic.<\/li>
      6. Cientista de Dados<\/a> at ENGINEERING.<\/li>
      7. Cientista de Dados Junior<\/a> at ENGINEERING.<\/li>
      8. Professor\/a de Data Science e\/ou Machine Learning<\/a> at Alura.<\/li>
      9. Analista de Dados<\/a> at Sympla.<\/li>
      10. Cientista de Dados<\/a> \/ Cientista de dados<\/a> at Sympla.<\/li>
      11. Analista de Business Intelligence<\/a> at Sympla.<\/li>
      12. Many data opportunities<\/a> at Atlantico.<\/li>
      13. Data Scientist<\/a> at RecrutaSimples.<\/li>
      14. Applications for 2020 Intern Program Are Now Open<\/a> at RStudio.<\/li>
      15. Computational Biologist<\/a> at NSU.
        The next opportunities (10+) are reserved for readers registered in the newsletter. By having registered, you will receive updates on the posts in the blog!
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