{"id":4740,"date":"2021-11-16T23:51:16","date_gmt":"2021-11-16T21:51:16","guid":{"rendered":"https:\/\/mribeirodantas.xyz\/blog\/?p=4740"},"modified":"2021-11-18T23:31:35","modified_gmt":"2021-11-18T21:31:35","slug":"best-links-of-the-week-87","status":"publish","type":"post","link":"https:\/\/mribeirodantas.xyz\/blog\/index.php\/2021\/11\/16\/best-links-of-the-week-87\/","title":{"rendered":"Best links of the week #87"},"content":{"rendered":"Reading time: <\/span> 3<\/span> minutes<\/b><\/span><\/span>\n

Best links of the week from September 2nd to November, 11th.<\/h3>\n\n\n\n
\"This<\/figure>\n\n\n\n

Links<\/h4>\n\n\n\n
  1. Creative Thinking<\/a> by Claude Shannon at Yousouf Naderi’s website<\/a>.<\/li>
  2. Latin Square Analysis of Variance<\/a> at StatsDirect<\/a>.<\/li>
  3. BAYESIAN NETWORKS AND THE SEARCH FOR CAUSALITY<\/a> at Ricardo Silva’s website<\/a>.<\/li>
  4. Triadic closure<\/a> at Wikipedia.<\/li>
  5. Balance theory<\/a> at Wikipedia.<\/li>
  6. The 5-Day Regression Challenge<\/a> by Rachael Tatman<\/a> at Kaggle<\/a>.<\/li>
  7. The 5-Day Data Challenge<\/a> by Rachael Tatman<\/a> at Kaggle<\/a>.<\/li>
  8. Intro to Machine Learning<\/a> at Kaggle Courses<\/a>.<\/li>
  9. Intermediate Machine Learning<\/a> at Kaggle Courses<\/a>.<\/li>
  10. Feature Engineering<\/a> at Kaggle Courses<\/a>.<\/li>
  11. Data Cleaning<\/a> at Kaggle Courses<\/a>.<\/li>
  12. Machine Learning Explainability<\/a> at Kaggle Courses<\/a>.<\/li>
  13. Fun, beginner-friendly datasets<\/a> at Kaggle<\/a>.<\/li>
  14. Datasets for regression analysis<\/a> at Kaggle<\/a>.<\/li>
  15. Yann LeCun\u2019s Deep Learning Course at CDS<\/a>.<\/li>
  16. <\/li><\/ol>\n\n\n\n\n\n\n\n

    Blog posts<\/h4>\n\n\n\n
    1. Invariance, Causality, and Robust Deep Learning<\/a> by Urwa Muaz<\/a> at Towards Data Science<\/a>.<\/li>
    2. Why assholes are more likely to be wrong<\/a> at Hugo Mercier’s Blog<\/a>.<\/li>
    3. Understanding Bias: A Pre-requisite For Trustworthy Results<\/a> at Adam Kelleher<\/a>‘s Medium blog.<\/li>
    4. Speed vs. Accuracy: When is Correlation Enough? When Do You Need Causation?<\/a> at Adam Kelleher<\/a>‘s Medium blog.<\/li>
    5. Causal Graph Inference<\/a> at Adam Kelleher<\/a>‘s Medium blog.<\/li>
    6. A Technical Primer On Causality<\/a> at Adam Kelleher<\/a>‘s Medium blog.<\/li>
    7. How do you correct selection bias?<\/a> at Adam Kelleher<\/a>‘s Medium blog.<\/li>
    8. Machine Learning PhD Applications \u2014 Everything You Need to Know<\/a> at Tim Dettmers<\/a>‘s Blog.<\/li>
    9. Graduate School Personal Statement<\/a> at MIT EECS Communication Lab<\/a>.<\/li>
    10. Tips on applying to a MS or a PhD at Stanford University<\/a>.<\/li>
    11. Questions to Ask a Prospective Ph.D. Advisor on Visit Day, With Thorough and Forthright Explanations<\/a> at at ML CMU Blog<\/a>.<\/li>
    12. Intuitive Understanding of Batch Normalization<\/a> at Gautham Kumaran<\/a>‘s Blog.<\/li>
    13. Into the Wild: Machine Learning In Non-Euclidean Spaces<\/a> at Stanford DAWN<\/a>.<\/li>
    14. Quando seus resultados n\u00e3o s\u00e3o significativos: um caso para teste de equival\u00eancia<\/a> at Rafael Valdece Sousa Bastos<\/a>‘s Medium.<\/li>
    15. The validity of psychological and educational tests<\/a> by Rafael Valdece Sousa Bastos<\/a> at Towards Data Science<\/a>.<\/li>
    16. Establishing Causality: Part 1<\/a> by Micha\u0142 Oleszak<\/a>Sep<\/a> at Towards Data Science<\/a>.<\/li>
    17. Establishing Causality: Part 2<\/a> by Micha\u0142 Oleszak<\/a>Sep<\/a> at Towards Data Science<\/a>.<\/li>
    18. Introducing Distance Correlation, a Superior Correlation Metric<\/a> by Terence Shin<\/a> at Towards Data Science<\/a>.<\/li>
    19. A Deep Conceptual Guide to Mutual Information<\/a> by Sean McClure<\/a> at Start It Up<\/a>.<\/li>
    20. Information Theory: A Gentle Introduction<\/a> by Douglas Hamilton<\/a> at Towards Data Science<\/a>.<\/li>
    21. Mutual Information: Prediction as Imitation<\/a> by Douglas Hamilton<\/a> at Towards Data Science<\/a>.<\/li>
    22. Information Theory: Principles and Apostasy<\/a> by Douglas Hamilton<\/a> at Towards Data Science<\/a>.<\/li>
    23. Collection of Do Calculus proofs\u2013now comes equipped with backdoor, frontdoor and napkin<\/a> at Quantum Bayesian Networks<\/a>.<\/li>
    24. Before Probability Distributions<\/a> by Diego Lopez Yse<\/a> at Towards Data Science<\/a>.<\/li>
    25. Probability concepts explained: Maximum likelihood estimation<\/a> by Jonny Brooks-Bartlett<\/a> at Towards Data Science<\/a>.<\/li>
    26. My reviews on Machine Learning, Data Science and Statistics books<\/a> at Merve Noyan<\/a>‘s blog.<\/li>
    27. An Introduction to Directed Acyclic Graphs (DAGs) for Data Scientists<\/a> by Dean Pleban at DAGsHub<\/a>‘s Blog.<\/li><\/ol>\n\n\n\n

      Positions available<\/h4>\n\n\n\n
      1. Postdoc\/research scientist\/technical staff position<\/a> at RIKEN AIP.<\/li>
      2. Postdoctoral Scholar<\/a> at Vision and Learning Lab (UC Merced).<\/li>
      3. Research internship opportunities<\/a> at AKASA.<\/li>
      4. Lectureship in Statistics<\/a> at Lancaster University.<\/li>
      5. Tenure-track faculty positions in computer and communication sciences<\/a> at EPFL.<\/li>
      6. Postdoctoral position in ML and Optimization<\/a> at CISPA.<\/li>
      7. PhD scholarship in the intersection optimization-learning-optimal control<\/a> at WIAS.<\/li>
      8. Postdoctoral position in the intersection optimization-learning-optimal control<\/a> at WIAS.<\/li>
      9. PhD internships in ML and Statistics<\/a> at Microsoft Research New England.<\/li>
      10. Engenheiro de Dados<\/a> at EnsineMe.<\/li>
      11. Analytics | Analista de Dados S\u00eanior<\/a> at flash.<\/li>
      12. Data Scientist<\/a> at Coodash.<\/li>
      13. Analista de Machine Learning | Remoto<\/a> at CyberLabs.<\/li>
      14. Engenheiro(a) S\u00eanior de MLOps<\/a> at CyberLabs.<\/li>
      15. Analytics Engineer<\/a> at Escale.<\/li>
      16. Lead Data Scientist<\/a> at Quanto.<\/li>
      17. Data Engineer<\/a> at Legiti.<\/li>
      18. Machine Learning Engineer<\/a> at Legiti.<\/li>
      19. Analista de Dados em Machine Learning S\u00eanior<\/a> at GupyTech.<\/li>
      20. Cientista de Dados Staff<\/a> at GupyTech.<\/li>
      21. Pessoa Engenheira de Dados<\/a> at Z1.<\/li>
      22. Cientista de Dados<\/a> at F\u00f3ton Inform\u00e1tica.<\/li>
      23. Gerente de Arquitetura e Dados<\/a> at Hprojekt.<\/li><\/ol>\n","protected":false},"excerpt":{"rendered":"

        Reading time: <\/span> 3<\/span> minutes<\/b><\/span><\/span>Best links of the week from September 2nd to November, 11th. Links Creative Thinking by Claude Shannon at Yousouf Naderi’s website. Latin Square Analysis of Variance at StatsDirect. BAYESIAN NETWORKS AND THE SEARCH FOR CAUSALITY at Ricardo Silva’s website. Triadic closure at Wikipedia. Balance theory at Wikipedia. The 5-Day Regression Challenge by Rachael Tatman at …<\/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_post_was_ever_published":false,"_jetpack_newsletter_access":"","_jetpack_dont_email_post_to_subs":false,"_jetpack_newsletter_tier_id":0,"_jetpack_memberships_contains_paywalled_content":false,"_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","enabled":false},"version":2}},"categories":[8],"tags":[28,11,63,15,200,10],"class_list":["post-4740","post","type-post","status-publish","format-standard","hentry","category-bestlinks","tag-data-science","tag-datascience","tag-machine-learning","tag-machinelearning","tag-ml","tag-statistics"],"jetpack_publicize_connections":[],"yoast_head":"\nBest links of the week #87 - 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\/11\/16\/best-links-of-the-week-87\/\" \/>\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 #87 - The Dataist Storyteller\" \/>\n<meta property=\"og:description\" content=\"Reading time: 3 minutesBest links of the week from September 2nd to November, 11th. 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Links Creative Thinking by Claude Shannon at Yousouf Naderi’s website. Latin Square Analysis of Variance at StatsDirect. BAYESIAN NETWORKS AND THE SEARCH FOR CAUSALITY at Ricardo Silva’s website. Triadic closure at Wikipedia. Balance theory at Wikipedia. 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