{"id":2060,"date":"2019-11-11T23:11:22","date_gmt":"2019-11-11T23:11:22","guid":{"rendered":"https:\/\/mribeirodantas.xyz\/blog\/?p=2060"},"modified":"2019-11-15T00:25:47","modified_gmt":"2019-11-15T00:25:47","slug":"best-links-of-the-week-44","status":"publish","type":"post","link":"https:\/\/mribeirodantas.xyz\/blog\/index.php\/2019\/11\/11\/best-links-of-the-week-44\/","title":{"rendered":"Best links of the week #44"},"content":{"rendered":"Reading time: <\/span> 3<\/span> minutes<\/b><\/span><\/span>\n

Best links of the week from 4th November to 10th November<\/h3>\n\n\n\n
\"This<\/figure>\n\n\n\n

Links<\/h4>\n\n\n\n
  1. Amazon makes its second digital health acquisition with Health Navigator<\/a> at Mobi Health News<\/a>.<\/li>
  2. Metasyntactic variable<\/a> at Wikipedia<\/a>.<\/li>
  3. Statistical Relationship: Definition, Examples<\/a> at Statistics How To<\/a>.<\/li>
  4. ggtext<\/a> at Claus Wilke<\/a>‘s GitHub.<\/li>
  5. Plot Ridge coefficients as a function of the regularization<\/a> at Scikit-Learn website<\/a>.<\/li>
  6. IBM pede regulamenta\u00e7\u00e3o para reconhecimento facial<\/a> at Olhar Digital<\/a>.<\/li>
  7. Indiferen\u00e7a \u00e0 verdade na era dos totalitarismos customizados<\/a> at Revista Quest\u00e3o de Ci\u00eancia<\/a>.<\/li>
  8. Google lan\u00e7a aplicativos para ajudar a passar menos tempo no celular<\/a> at TechTudo<\/a>.<\/li>
  9. Laura: a intelig\u00eancia artificial que j\u00e1 salvou 12 mil vidas no Brasil<\/a> at Endeavor<\/a>.<\/li>
  10. Por que o novo filme do \u2018Exterminador do Futuro\u2019 est\u00e1 irritando pesquisadores de intelig\u00eancia artificial<\/a> at BBC Brasil<\/a>.<\/li>
  11. Esta empresa criou uma intelig\u00eancia artificial que funciona como a humana<\/a> at \u00c9poca Neg\u00f3cios<\/a>.<\/li><\/ol>\n\n\n\n\n\n\n\n

    Blog\/posts<\/h4>\n\n\n\n
    1. Where did the least-square come from?<\/a> by Tirthajyoti Sarkar<\/a> at Towards Data Science<\/a>.<\/li>
    2. Introducing Model Bias and Variance<\/a> by Peter Grant<\/a> at Towards Data Science<\/a>.<\/li>
    3. Linear Regression \u2014 Detailed View<\/a> by Saishruthi Swaminathan<\/a> at Towards Data Science<\/a>.<\/li>
    4. Simple and Multiple Linear Regression in Python<\/a> by Adi Bronshtein<\/a> at Towards Data Science<\/a>.<\/li>
    5. Generalized Linear Models in R, Part 1: Calculating Predicted Probability in Binary Logistic Regression<\/a> at The Analysis Factor<\/a>.<\/li>
    6. Generalized Linear Models in R, Part 2: Understanding Model Fit in Logistic Regression Output<\/a> at The Analysis Factor<\/a>.<\/li>
    7. Generalized Linear Models in R, Part 3: Plotting Predicted Probabilities<\/a> at The Analysis Factor<\/a>.<\/li>
    8. Generalized Linear Models (GLMs) in R, Part 4: Options, Link Functions, and Interpretation<\/a> at The Analysis Factor<\/a>.<\/li>
    9. PRACTICAL MACHINE LEARNING: RIDGE REGRESSION VS. LASSO<\/a> at Coding Startups<\/a>.<\/li>
    10. Regularization: Ridge, Lasso and Elastic Net<\/a> by Micha\u0142 Oleszak<\/a> at DataCamp Community Tutorials<\/a>.<\/li>
    11. Regularization: the path to bias-variance trade-off<\/a> by HAFEEZ JIMOH<\/a> at Towards Data Science<\/a>.<\/li>
    12. The Difference Between Logistic and Probit Regression<\/a> at The Analysis Factor<\/a>.<\/li>
    13. Five Extensions of the General Linear Model<\/a> at The Analysis Factor<\/a>.<\/li>
    14. How to break regression<\/a> by Solomon Messing<\/a> at Decoded \/ Pew Research Center<\/a>.<\/li>
    15. How to create confounders with regression: a lesson from causal inference<\/a> by Ben Ogorek<\/a> at R-Bloggers<\/a> (or in his blog at Anything But R-Bitrary<\/a>.<\/li>
    16. Three ways to call C\/C++ from R<\/a> at Anything But R-Bitrary<\/a>.<\/li>
    17. Random regression coefficients using lme4<\/a> at Anything But R-Bitrary<\/a>.<\/li><\/ol>\n\n\n\n

      Videos<\/h4>\n\n\n\n
      1. Machine Learning Fundamentals: Cross-Validation<\/a> at StatQuest with Josh Starmer<\/a>.<\/li>
      2. How to Calculate R Squared Using Regression Analysis<\/a> at statisticsfun<\/a>,<\/li>
      3. Regularization Part 1: Ridge Regression<\/a> at StatQuest with Josh Starmer<\/a>.<\/li>
      4. Regularization Part 2: Lasso Regression<\/a> at StatQuest with Josh Starmer<\/a>.<\/li>
      5. Regularization Part 3: Elastic Net Regression<\/a> at StatQuest with Josh Starmer<\/a>.<\/li>
      6. Fundamentos de Aprendizagem de M\u00e1quina: Vi\u00e9s e Vari\u00e2ncia<\/a> at StatQuest with Josh Starmer<\/a>.<\/li><\/ol>\n\n\n\n

        Podcast<\/h4>\n\n\n\n
        1. Casual Inference: Talking Target Trials with Miguel Hernan | Episode 01<\/a> at Casual Inference Podcast<\/a>.<\/li><\/ol>\n\n\n\n

          Positions available<\/h4>\n\n\n\n
          1. Research Chair in Computer Science<\/a> at Concordia University.<\/li>
          2. Senior Research Associate in High-Dimensional Longitudinal Methods<\/a> at Lancaster University.<\/li>
          3. 2 Postdoctoral research opportunities in Privacy-Preserving Machine Learning and Probabilistic Modelling<\/a> at the University of Helsinki.<\/li>
          4. Research Associate Position in Probabilistic Modelling for Low-Cost Air Pollution Monitoring<\/a> at the University of Sheffield.<\/li>
          5. Assistant Professor in Human-Computer Interaction and Music<\/a> at the New York University.<\/li>
          6. Research Associate Position in Learning Agents and Robots<\/a> at RISE.<\/li>
          7. Cientista de Dados (S\u00eanior)<\/a> at Gupy Tech.<\/li>
          8. Enterprise Data Engineer<\/a> at 10x GENOMICS.<\/li>
          9. Tenure-track positions in Statistics<\/a> at Wake Forest University.<\/li>
          10. Tenure-Track Faculty Position in Data Science<\/a> at the University of Kentucky.<\/li>
          11. Two Tenure track positions in Mathematical Statistics as Assistant\/Associate professor<\/a> at University of Amsterdam.<\/li>
          12. Data Engineer<\/a> at ENGIE Cofely France.<\/li>
          13. Data Scientist<\/a> at Fujitsu France.<\/li>
          14. CDI \u2013 Data engineer \u2013 Python<\/a> at HireFirst.<\/li>
          15. Data Engineer<\/a> at Contentsquare.
            In order to see the full list of opportunities (30+), you have to register for the newsletter. By doing this, you will receive updates on the posts in the blog!
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