{"id":1404,"date":"2019-08-12T13:18:09","date_gmt":"2019-08-12T13:18:09","guid":{"rendered":"https:\/\/mribeirodantas.xyz\/blog\/?p=1404"},"modified":"2019-08-12T13:18:19","modified_gmt":"2019-08-12T13:18:19","slug":"best-links-of-the-week-31","status":"publish","type":"post","link":"https:\/\/mribeirodantas.xyz\/blog\/index.php\/2019\/08\/12\/best-links-of-the-week-31\/","title":{"rendered":"Best links of the week #31"},"content":{"rendered":"Reading time: <\/span> 2<\/span> minutes<\/b><\/span><\/span>\n

Best links of the week from 5th August to 11th August<\/h3>\n\n\n\n
\"\"
Source: here<\/a>.<\/figcaption><\/figure>\n\n\n\n

Links<\/h4>\n\n\n\n
  1. randomizr: R Package for randomized experiments<\/a>.<\/li>
  2. Bayes’rule: Guide (course with several different levels)<\/a>.<\/li>
  3. Extracting Brazilian schools census data with R<\/a> at Fernando Barbalho’s gists<\/a>.<\/li>
  4. Download all data from DATASUS (several Brazilian health-related datasets) with R<\/a> at Fernando Barbalho’s gists<\/a>.<\/li><\/ol>\n\n\n\n\n\n\n\n

    Blog\/posts<\/h4>\n\n\n\n
    1. Statistics & Probability: Fundamentals 1<\/a> at Felix Laumann<\/a>‘s Medium account.<\/li>
    2. Statistics & Probability: Fundamentals 2<\/a> at Felix Laumann<\/a>‘s Medium account.<\/li>
    3. Probabilistic Graphical Models: Fundamentals<\/a> at Felix Laumann<\/a>‘s Medium account.<\/li>
    4. Inference in Probabilistic Models: Monte Carlo and variational methods<\/a> at Felix Laumann<\/a>‘s Medium account.<\/li>
    5. When machine learning meets complexity: why Bayesian deep learning is unavoidable<\/a> at Felix Laumann<\/a>‘s Medium account.<\/li>
    6. How Bayesian methods embody Occam\u2019s razor<\/a> at Felix Laumann<\/a>‘s Medium account.<\/li>
    7. Probability Learning I: Bayes’ Theorem<\/a> at Towards Data Science<\/a>.<\/li>
    8. General vs Narrow AI<\/a> at HackerNoon<\/a>.<\/li>
    9. Probability concepts explained: Introduction<\/a> by Jonny Brooks-Bartlett<\/a> at Towards Data Science<\/a>.<\/li>
    10. Probability concepts explained: Rules of probability (introduction part 2) <\/a>by Jonny Brooks-Bartlett<\/a> at Towards Data Science<\/a>.<\/li>
    11. Probability concepts explained: probability distributions (introduction part 3)<\/a> by Jonny Brooks-Bartlett<\/a> at Towards Data Science<\/a>.<\/li>
    12. Common Probability Distributions: The Data Scientist\u2019s Crib Sheet<\/a> at Sean Owen<\/a>.<\/li><\/ol>\n\n\n\n

      Podcast<\/h4>\n\n\n\n
      1. Cause & Effect: A Conversation with Judea Pearl<\/a> at Sam Harris’ Making Sense Podcast (#164)<\/a>. <\/li>
      2. Fisiopatologia do C\u00e2ncer (Reimagine o C\u00e2ncer #03)<\/a> at SciCast, Portal Deviante<\/a>.<\/li><\/ol>\n\n\n\n

        Scientific article<\/h4>\n\n\n\n
        1. Ten simple rules for writing and sharing computational analyses in Jupyter Notebooks<\/a> at PLOS Computational Biology<\/a>.<\/li><\/ol>\n\n\n\n

          Videos<\/h4>\n\n\n\n
          1. Maximum Likelihood Estimation in R I<\/a> at Vidya-mitra<\/a> YouTube channel.<\/li>
          2. Maximum Likelihood Estimation in R II<\/a> at Vidya-mitra<\/a> YouTube channel.<\/li>
          3. M\u00e1xima Verossimilhan\u00e7a para a Distribui\u00e7\u00e3o Normal, passo a passo!<\/a> at StatQuest with Josh Starmer<\/a>‘s YouTube channel.<\/li>
          4. A visual guide to Bayesian thinking<\/a> at Julia Galef<\/a>‘s YouTube channel.<\/li><\/ol>\n\n\n\n

            Positions available<\/h4>\n\n\n\n
            1. Senior Backend Developer \/ Data Engineer<\/a> at AdMobilize.<\/li>
            2. Cientista de Dados<\/a> at Cervejaria Ambev.<\/li>
            3. Especialista de Dados<\/a> at ARPO Talent Connections.<\/li>
            4. DBA \/ Arquiteto de Banco de Dados S\u00eanior<\/a> at M\u00e9liuz.<\/li>
            5. Desenvolvedor(a) Front-End S\u00eanior<\/a> at M\u00e9liuz.<\/li>
            6. Desenvolvedor(a) Web Analytics<\/a> at DP6.<\/li>
            7. Consultor(a) de Digital Analytics<\/a> at DP6.<\/li>
            8. Desenvolvedor(a) Python<\/a> at Jeitto.<\/li>
            9. Engenheiro de Dados<\/a> at Resource IT.<\/li>
            10. Data Scientist – Vis\u00e3o computacional<\/a> at Kognita Lab.<\/li>
            11. Data Scientist \/ Cientista de dados (foco em NLP)<\/a> at Kognita Lab.<\/li>
            12. Est\u00e1gio em Data Science<\/a> at Kognita Lab.<\/li>
            13. Big Data Software Engineer<\/a> at Epam Systems.<\/li>
            14. Seguran\u00e7a da Informa\u00e7\u00e3o – Prote\u00e7\u00e3o de dados<\/a> at Beijaflore Consultoria.<\/li>
            15. Research Staff Position<\/a> at Sandia National Laboratories.<\/li>
            16. Ph.D. opportunity in Computational Linguistics<\/a> at Saarland University.<\/li>
            17. Tenure Track Faculty Positions in Artificial Intelligence<\/a> at Oregon State University.<\/li>
            18. Ph.D. opportunity on NLP and statistical relational learning<\/a> at the University of Edinburgh.<\/li>
            19. Ph.D. opportunity in Artificial Intelligence for Future Society Smart Cities<\/a> at the University of Southampton.<\/li>
            20. Ph.D. opportunity in Machine Learning for Stress and Fatigue Detection in Ship Crews<\/a> at the University of Southampton.<\/li>
            21. Machine Learning Researcher Positions<\/a> at Arm’s ML Research Group in Austin, USA.<\/li>
            22. Several research interns\/associate positions<\/a> at Honda Research Institute.<\/li>
            23. Research Fellow in Computer Vision<\/a> at Monash University.<\/li><\/ol>\n","protected":false},"excerpt":{"rendered":"

              Reading time: <\/span> 2<\/span> minutes<\/b><\/span><\/span>This release of my best links of the week comes with A LOT of knowledge on bayesian reasoning and statistics. But that’s not it, there are also data for you to analyze, podcasts episodes and SEVERAL opportunities! \ud83d\ude42<\/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":[92,12,16,9,13,28,63,94,10],"class_list":["post-1404","post","type-post","status-publish","format-standard","hentry","category-bestlinks","tag-bayes","tag-bayesianism","tag-cancer","tag-causality","tag-data","tag-data-science","tag-machine-learning","tag-r-packages","tag-statistics"],"jetpack_publicize_connections":[],"yoast_head":"\nBest links of the week #31 - 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\/2019\/08\/12\/best-links-of-the-week-31\/\" \/>\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 #31 - The Dataist Storyteller\" \/>\n<meta property=\"og:description\" content=\"Reading time: 2 minutesThis release of my best links of the week comes with A LOT of knowledge on bayesian reasoning and statistics. 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