{"id":4652,"date":"2021-09-22T03:28:01","date_gmt":"2021-09-22T01:28:01","guid":{"rendered":"https:\/\/mribeirodantas.xyz\/blog\/?p=4652"},"modified":"2021-09-22T03:28:05","modified_gmt":"2021-09-22T01:28:05","slug":"best-links-of-the-week-86","status":"publish","type":"post","link":"https:\/\/mribeirodantas.xyz\/blog\/index.php\/2021\/09\/22\/best-links-of-the-week-86\/","title":{"rendered":"Best links of the week #86"},"content":{"rendered":"Reading time: <\/span> 3<\/span> minutes<\/b><\/span><\/span>\n

Best links of the week from August 2nd to September 21st<\/h3>\n\n\n\n
\"This<\/figure>\n\n\n\n

Links<\/h4>\n\n\n\n
  1. Maximum Likelihood Estimates<\/a> by Jeremy Orloff and Jonathan Bloom.<\/li>
  2. Moravec’s paradox<\/a> at Wikipedia<\/a>.<\/li>
  3. Parrondo’s paradox<\/a> at Wikipedia<\/a>.<\/li>
  4. R-squared Cautions<\/a> at STAT 462 (Applied Regression Analysis), PennState University<\/a>.<\/li>
  5. Spearman\u2019s correlation<\/a>.<\/li>
  6. CausalCity: Introducing a high-fidelity simulation with agency for advancing causal reasoning in machine learning<\/a> at Microsoft Research Blog<\/a>.<\/li>
  7. The Most Dangerous Equation<\/a> at American Scientist<\/a>. More here<\/a> and here<\/a>.<\/li>
  8. One day course on causal inference, MPI-EVA 9 September 2021<\/a> at Richard McElreath<\/a>‘s GitHub.<\/li>
  9. The cost of dichotomising continuous variables<\/a>, published in BMJ, at PubMed Central<\/a>.<\/li>
  10. How Computationally Complex Is a Single Neuron?<\/a> at QuantaMagazine<\/a>.<\/li>
  11. Focus on Peer Review Course<\/a> at Nature Masterclasses<\/a>.<\/li><\/ol>\n\n\n\n\n\n\n\n

    Blog posts<\/h4>\n\n\n\n
    1. What Is TF-IDF?<\/a> at MonkeyLearn<\/a>.<\/li>
    2. The Beginner\u2019s Guide to Text Vectorization<\/a> at MonkeyLearn<\/a>.<\/li>
    3. Naive Bayes and Text Classification<\/a> at Sebastian Raschka<\/a>.<\/li>
    4. Neural Network: Architecture, Components & Top Algorithms<\/a> at UpGrad<\/a>.<\/li>
    5. Why Initialize a Neural Network with Random Weights?<\/a> at Machine Learning Mastery<\/a>.<\/li>
    6. Hacks, IA\u2019s e manipula\u00e7\u00e3o humana<\/a> at Portal Deviante<\/a>.<\/li>
    7. Neural Network Models in R<\/a> at DataCamp Tutorial<\/a>.<\/li>
    8. Demystifying Mathematical Concepts for Deep Learning<\/a> at DataCamp Tutorial<\/a>.<\/li>
    9. Deduce the Number of Layers and Neurons for ANN<\/a> at DataCamp Tutorial<\/a>.<\/li>
    10. A Gentle Introduction to Exploding Gradients in Neural Networks<\/a> at Machine Learning Mastery<\/a>.<\/li>
    11. How to Fix the Vanishing Gradients Problem Using the ReLU<\/a> at Machine Learning Mastery<\/a>.<\/li>
    12. A Gentle Introduction to the Rectified Linear Unit (ReLU)<\/a> at Machine Learning Mastery<\/a>.<\/li>
    13. The New Base Pipe<\/a> at MyKo101<\/a>.<\/li>
    14. ETL vs ELT Explained<\/a> at The Grouparoo Blog<\/a>.<\/li>
    15. The Mathematics Behind Deep Learning<\/a> by Trist’n Joseph<\/a> at Towards Data Science<\/a>.<\/li>
    16. The Unreasonable Ineffectiveness of Deep Learning on Tabular Data<\/a> by Paul Tune<\/a> at Towards Data Science<\/a>.<\/li>
    17. SHAP Values Explained Exactly How You Wished Someone Explained to You<\/a> by Samuele Mazzanti<\/a> at Towards Data Science<\/a>. <\/li>
    18. Black-Box models are actually more explainable than a Logistic Regression<\/a> by Samuele Mazzanti<\/a> at Towards Data Science<\/a>.<\/li>
    19. Increasing developer happiness with GitHub code scanning<\/a> at GitHub blog<\/a>.<\/li>
    20. What can Avengers: Endgame teach us about Git?<\/a> at Lj Miranda<\/a>‘s Blog.<\/li><\/ol>\n\n\n\n

      Videos<\/h4>\n\n\n\n
      1. StatQuest: Maximum Likelihood, clearly explained!!!<\/a> at StatQuest with Josh Starmer<\/a>.<\/li>
      2. Maximum Likelihood for the Exponential Distribution, Clearly Explained! V2.0<\/a> at StatQuest with Josh Starmer<\/a>.<\/li>
      3. Maximum Likelihood for the Binomial Distribution, Clearly Explained!!!<\/a> at StatQuest with Josh Starmer<\/a>.<\/li>
      4. Parte 1 – Regress\u00e3o Linear – \u00c9 a sua chance! Agora ou nunca! – Prof. Adriana Silva<\/a> at EstaTiDados<\/a>.<\/li>
      5. Parte 2 – Regress\u00e3o Linear – \u00c9 a sua chance! Agora ou nunca! – Prof. Adriana Silva<\/a> at EstaTiDados<\/a>.<\/li>
      6. Parte 3 – Regress\u00e3o Log\u00edstica – \u00c9 a sua chance! Agora ou nunca! – Prof. Adriana Silva<\/a> at EstaTiDados<\/a>.<\/li>
      7. Estreia da S\u00e9rie Teoria de Conjuntos para Estat\u00edstica – Teoria de conjuntos #1<\/a> at A Ci\u00eancia da Estat\u00edstica<\/a>.<\/li>
      8. Axiomas da EXTENS\u00c3O e da ESPECIFICA\u00c7\u00c3O (Pertencimento, Igualdade e Inclus\u00e3o) -Teoria de Conjuntos #2<\/a> at A Ci\u00eancia da Estat\u00edstica<\/a>.<\/li>
      9. Axiomas do PAR e da UNI\u00c3O (uni\u00e3o, interse\u00e7\u00e3o, diferen\u00e7a, Complementar) – Teoria de Conjuntos #3<\/a> at A Ci\u00eancia da Estat\u00edstica<\/a>.<\/li>
      10. Axioma da POT\u00caNCIA (Conjuntos das partes, produtos cartesianos e rela\u00e7\u00f5es) – Teoria de conjuntos #4<\/a> at A Ci\u00eancia da Estat\u00edstica<\/a>.<\/li>
      11. FUN\u00c7\u00d5ES injetoras, sobrejetoras e bijetoras (IMAGEM e IMAGEM INVERSA) – Teoria de conjuntos #5<\/a> at A Ci\u00eancia da Estat\u00edstica<\/a>.<\/li>
      12. Cost Function in Neural Network | Types of Cost function we use in different applications<\/a> at Coding Lane<\/a>.<\/li>
      13. What is Activation function in Neural Network ? Types of Activation Function in Neural Network<\/a> at Coding Lane<\/a>.<\/li>
      14. Mas o que *\u00e9* uma Rede Neural? | Deep learning, cap\u00edtulo 1<\/a> at 3Blue1Brown<\/a>‘s YouTube channel.<\/li>
      15. Causal Discovery Part 1 by Bernhard Sch\u00f6lkopf<\/a> at MLSS Africa’s YouTube channel<\/a>.<\/li>
      16. Causal Discovery Part 2 by Bernhard Sch\u00f6lkopf<\/a> at MLSS Africa’s YouTube channel<\/a>.<\/li>
      17. Spearman’s Rank-Order Correlation<\/a> at Laerd Statistics<\/a>.<\/li>
      18. Spearman’s Rank-Order Correlation using SPSS Statistics<\/a> at Laerd Statistics<\/a>.<\/li>
      19. An Ode To R-Squared<\/a> by Callum Ballard<\/a> at Towads Data Science<\/a>.<\/li>
      20. Spearman’s Rank Correlation part 1<\/a> at <\/a>ECOHOLICS – Largest Platform for Economics<\/a>.<\/li>
      21. Spearman’s Rank Correlation part 2<\/a> at <\/a>ECOHOLICS – Largest Platform for Economics<\/a>.<\/li>
      22. <\/a><\/a>Spearman’s Rank Correlation part 3 at ECOHOLICS – Largest Platform for Economics<\/a>.<\/li>
      23. Machine Learning Experiments with DVC (Hands-On Tutorial!)<\/a> at DVCorg<\/a>‘s YouTube channel.<\/li>
      24. Checkpoints<\/a> at DVCorg<\/a>‘s YouTube channel.<\/li>
      25. Experiments<\/a> at DVCorg<\/a>‘s YouTube channel.<\/li>
      26. Deep Learning Basics: Introduction and Overview<\/a> at Lex Fridman<\/a>‘s YouTube channel.<\/li><\/ol>\n\n\n\n

        Positions available<\/h4>\n\n\n\n
        1. PostDoc in Protein Biochemistry<\/a> at MPI CBG.<\/li>
        2. PhD student in Computational Biology<\/a> at MPI CBG.<\/li>
        3. Postdoctoral Position in Computational Biology<\/a> at MPI CBG.<\/li>
        4. Postdoctoral Position in Cell Biology<\/a> at MPI CBG.<\/li>
        5. PhD scholarship in “AI for electricity market design”<\/a> at DTU.<\/li>
        6. Engineer R&D<\/a> at SteelSeries.<\/li>
        7. Postdoctoral opportunity on (hierarchical) multi-agent reinforcement learning<\/a> at Northeastern University.<\/li>
        8. Machine Learning Fairness Research PhD Intern<\/a> at Tiktok.<\/li>
        9. Assistant Professor – Computational Linguistics<\/a> at University of Toronto Scarborough.<\/li>
        10. Several postdoctoral research positions in\u00a0Bayesian\u00a0optimization\u00a0and\/or simulation-based optimization<\/a> in Montreal.<\/li>
        11. Postdoc in Computer Vision\/Deep Learning: video monitoring of insect pollinators<\/a> at the University of Puerto Rico.<\/li>
        12. Open positions for AI professors<\/a> at FHWS.<\/li>
        13. PhD scholarship in NLP<\/a> at James Cook University.<\/li>
        14. Assistant Professor – AI<\/a> at Iowa State University.<\/li>
        15. Open Postdoc Position Medical AI<\/a> at Med Uni Graz.<\/li>
        16. Staff Data Scientist<\/a> at FireEye.<\/li>
        17. Cientista de Dados | Big Data & AI<\/a> at Grupo Globo.<\/li>
        18. Pessoa Engenheira de Dados | Big Data & AI<\/a> at Grupo Globo.<\/li>
        19. Pessoa Engenheira de Machine Learning | Big Data & AI<\/a> at Grupo Globo.<\/li>
        20. Analista de Dados S\u00eanior<\/a> at OLX.<\/li><\/ol>\n\n\n\n

          <\/p>\n","protected":false},"excerpt":{"rendered":"

          Reading time: <\/span> 3<\/span> minutes<\/b><\/span><\/span>Best links of the week from August 2nd to September 21st Links Maximum Likelihood Estimates by Jeremy Orloff and Jonathan Bloom. Moravec’s paradox at Wikipedia. Parrondo’s paradox at Wikipedia. R-squared Cautions at STAT 462 (Applied Regression Analysis), PennState University. Spearman\u2019s correlation. CausalCity: Introducing a high-fidelity simulation with agency for advancing causal reasoning in machine learning …<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_uag_custom_page_level_css":"","_jetpack_newsletter_access":"","_jetpack_dont_email_post_to_subs":false,"_jetpack_newsletter_tier_id":0,"_jetpack_memberships_contains_paywalled_content":false,"_jetpack_feature_clip_id":0,"_jetpack_memberships_contains_paid_content":false,"footnotes":"","jetpack_publicize_message":"","jetpack_publicize_feature_enabled":true,"jetpack_social_post_already_shared":true,"jetpack_social_options":{"image_generator_settings":{"template":"highway","default_image_id":0,"font":"","enabled":false},"version":2},"jetpack_post_was_ever_published":false},"categories":[8],"tags":[],"class_list":["post-4652","post","type-post","status-publish","format-standard","hentry","category-bestlinks"],"yoast_head":"\nBest links of the week #86 - The Dataist Storyteller<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/mribeirodantas.xyz\/blog\/index.php\/2021\/09\/22\/best-links-of-the-week-86\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Best links of the week #86 - The Dataist Storyteller\" \/>\n<meta property=\"og:description\" content=\"Reading time: 3 minutesBest links of the week from August 2nd to September 21st Links Maximum Likelihood Estimates by Jeremy Orloff and Jonathan Bloom. 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Moravec’s paradox at Wikipedia. Parrondo’s paradox at Wikipedia. R-squared Cautions at STAT 462 (Applied Regression Analysis), PennState University. Spearman\u2019s correlation. CausalCity: Introducing a high-fidelity simulation with agency for advancing causal reasoning…","jetpack_sharing_enabled":true,"jetpack_shortlink":"https:\/\/wp.me\/paw9jx-1d2","jetpack-related-posts":[{"id":152,"url":"https:\/\/mribeirodantas.xyz\/blog\/index.php\/2019\/01\/28\/best-links-of-the-week-3\/","url_meta":{"origin":4652,"position":0},"title":"Best links of the week #3","author":"mribeirodantas","date":"January 28, 2019","format":false,"excerpt":"Best links of the week from 21th January to 27th January. Links The bioinformatics chat is a podcast about computational biology, bioinformatics, and next generation sequencing.Trilha de estudos de Data Science at fcqueiroz's GitHub.Jonas Salk: Good at Virology, Bad at Economics at Slate.Why is Data Preprocessing required? at Ques10.What bioRxiv\u2019s\u2026","rel":"","context":"In "BestLinks"","block_context":{"text":"BestLinks","link":"https:\/\/mribeirodantas.xyz\/blog\/index.php\/category\/bestlinks\/"},"img":{"alt_text":"","src":"","width":0,"height":0},"classes":[]},{"id":4516,"url":"https:\/\/mribeirodantas.xyz\/blog\/index.php\/2021\/04\/20\/best-links-of-the-week-84\/","url_meta":{"origin":4652,"position":1},"title":"Best links of the week #84","author":"mribeirodantas","date":"April 20, 2021","format":false,"excerpt":"Best links of the week from 13rd April to 19th April Links Causal Generative Machine Learning Minicourse at Altdeep.BELIEF IN THE LAW OF SMALL NUMBERS by Amos Tversky and Daniel Kahneman.Why Some Models Leak Data at PAIR EXPLORABLES.Moving Trends and Statistics in the US During the COVID-19 Pandemic at Moving\u2026","rel":"","context":"In "BestLinks"","block_context":{"text":"BestLinks","link":"https:\/\/mribeirodantas.xyz\/blog\/index.php\/category\/bestlinks\/"},"img":{"alt_text":"","src":"","width":0,"height":0},"classes":[]},{"id":4319,"url":"https:\/\/mribeirodantas.xyz\/blog\/index.php\/2020\/09\/15\/best-links-of-the-week-78\/","url_meta":{"origin":4652,"position":2},"title":"Best links of the week #78","author":"mribeirodantas","date":"September 15, 2020","format":false,"excerpt":"Best links of the week from 7th September to 13th September Links What are the various scenarios where we get a negative R squared in a (linear) regression model? at Quora. Blog posts Quem seguir para acompanhar Machine Learning e AI no Twitter? at Machina Economicus.Now Nubank\u2019s Data Scientists have\u2026","rel":"","context":"In "BestLinks"","block_context":{"text":"BestLinks","link":"https:\/\/mribeirodantas.xyz\/blog\/index.php\/category\/bestlinks\/"},"img":{"alt_text":"","src":"","width":0,"height":0},"classes":[]},{"id":216,"url":"https:\/\/mribeirodantas.xyz\/blog\/index.php\/2019\/02\/04\/best-links-of-the-week-4\/","url_meta":{"origin":4652,"position":3},"title":"Best links of the week #4","author":"mribeirodantas","date":"February 4, 2019","format":false,"excerpt":"Best links of the week from 28th January to 3rd February. Links Upload your CV and get suggestions and corrections at CV Compiler.Regression toward the mean at Wikipedia.Free and open resource with Machine Learning papers, code and evaluation tables at Papers With Code.Machine Learning Timeline at Leandro Mineti's GitHub.V\u00e1rios algoritmos\u2026","rel":"","context":"In "BestLinks"","block_context":{"text":"BestLinks","link":"https:\/\/mribeirodantas.xyz\/blog\/index.php\/category\/bestlinks\/"},"img":{"alt_text":"","src":"","width":0,"height":0},"classes":[]},{"id":337,"url":"https:\/\/mribeirodantas.xyz\/blog\/index.php\/2019\/03\/04\/best-links-of-the-week-8\/","url_meta":{"origin":4652,"position":4},"title":"Best links of the week #8","author":"mribeirodantas","date":"March 4, 2019","format":false,"excerpt":"Best links of the week from 25th February to 3rd March. Links I don't like notebooks at Jupyter Conference 2018 by Joel Grus.Twitter thread on Regression to the Mean Bias in a published paper at Andrew Althouse Twitter feed.The hipster effect: Why anti-conformists always end up looking the same at\u2026","rel":"","context":"In "BestLinks"","block_context":{"text":"BestLinks","link":"https:\/\/mribeirodantas.xyz\/blog\/index.php\/category\/bestlinks\/"},"img":{"alt_text":"","src":"","width":0,"height":0},"classes":[]},{"id":4235,"url":"https:\/\/mribeirodantas.xyz\/blog\/index.php\/2020\/09\/01\/best-links-of-the-week-76\/","url_meta":{"origin":4652,"position":5},"title":"Best links of the week #76","author":"mribeirodantas","date":"September 1, 2020","format":false,"excerpt":"Best links of the week from 24th August to 30th August Links Difference-in-Difference Estimation at Columbia Public Health.Cluster Analysis Using K-Means at Columbia Public Health.Discrete Choice Analysis at Columbia Public Health.Exploratory Factor Analysis at Columbia Public Health.Instrumental Variables at Columbia Public Health.Spline Regression at Columbia Public Health.Principal Components Analysis at\u2026","rel":"","context":"In "BestLinks"","block_context":{"text":"BestLinks","link":"https:\/\/mribeirodantas.xyz\/blog\/index.php\/category\/bestlinks\/"},"img":{"alt_text":"","src":"","width":0,"height":0},"classes":[]}],"jetpack_likes_enabled":true,"_links":{"self":[{"href":"https:\/\/mribeirodantas.xyz\/blog\/index.php\/wp-json\/wp\/v2\/posts\/4652","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/mribeirodantas.xyz\/blog\/index.php\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/mribeirodantas.xyz\/blog\/index.php\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/mribeirodantas.xyz\/blog\/index.php\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/mribeirodantas.xyz\/blog\/index.php\/wp-json\/wp\/v2\/comments?post=4652"}],"version-history":[{"count":65,"href":"https:\/\/mribeirodantas.xyz\/blog\/index.php\/wp-json\/wp\/v2\/posts\/4652\/revisions"}],"predecessor-version":[{"id":4737,"href":"https:\/\/mribeirodantas.xyz\/blog\/index.php\/wp-json\/wp\/v2\/posts\/4652\/revisions\/4737"}],"wp:attachment":[{"href":"https:\/\/mribeirodantas.xyz\/blog\/index.php\/wp-json\/wp\/v2\/media?parent=4652"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/mribeirodantas.xyz\/blog\/index.php\/wp-json\/wp\/v2\/categories?post=4652"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/mribeirodantas.xyz\/blog\/index.php\/wp-json\/wp\/v2\/tags?post=4652"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}