Best links of the week #66

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Best links of the week from 20th April to 26th April

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Links

  1. COVID-19 na Perspectiva Geográfica e Estatística at IBGE.
  2. Postmortem documentation at Wikipedia.
  3. Pesquisa de datasets do Google at Dados Abertos.
  4. Preocupações sobre abertura de dados e respostas que têm se mostrado efetivas at Dados Abertos.
  5. COVID-19 Analysis Repository at Christian S. Perone’s GitHub.

Blog posts

  1. Accountability, Core Machine Learning e Machine Learning Operations at Flavio Cesio’s Blog.
  2. Machine Learning e o modelo de queijo suíço: falhas ativas e condições latentes at Flavio Cesio’s Blog.
  3. Efeitos do viés de seleção amostral: um estudo de caso at Alexandre Patriota’s Medium.
  4. PRECISAMOS DAS ESTATÍSTICAS DO IBGE PARA AJUDAR A VENCER O COVID-19 at Simon’s Site.
  5. Were 21% of New York City residents really infected with the novel coronavirus? by Cassie Kozyrkov at Towards Data Science.
  6. A Decision Scientist’s 10 Dos & Don’ts for COVID-19 at Towards Data Science.
  7. The Big Data of Big Hair at The Pudding.
  8. Por que calcular variâncias de estimativas? at Something Random.
  9. Por que é tão difícil calcular variância com amostras complexas? at Something Random.

Podcasts

  1. O que são os Preprints e como estão sendo usados no contexto da Pandemia? at Spin de Notícias.

Videos

  1. Your brain is not a Bayes net (and why that matters) at Julia Galef‘s YouTube channel.
  2. The era of blind faith in big data must end at TED Talks.
  3. Como praticar eficazmente… para quase qualquer coisa TED-Ed‘s YouTube channel.

Positions available

  1. Principal Data Scientist at VanHack.
  2. Cientista de Dados at Solides.
  3. ANALISTA DE ENGENHARIA DE DADOS at Banco Inter.
  4. ARQUITETO DE DADOS at Banco Inter.
  5. Computational Linguist at the South African Centre for Digital Language Resources.
  6. PROFESSORSHIP (junior/senior): EMBODIED LEARNING MACHINES at KU Leuven.
  7. Open Ph.D. positions in Artificial Intelligence and Pervasive Computing at the University of Deusto.
  8. Postdoctoral position in Knowledge Graphs and Natural Language Processing at Stanford University.
  9. Postdoctoral Position in Network Analytics and Machine Learning at Stanford University.
  10. Computer Vision Researcher Role at Fast Paced Startup.
  11. Ph.D. scholarships in Artificial Intelligence and Language, Communication and the Brain at ILCB.
  12. Ph.D. Position in Fair AI at Chalmers.
  13. Postdoctoral position in Information, Fairness and Socially Beneficial AI at Chalmers.
  14. Two Postdoctoral Fellowship Positions in Ophthalmic Data Mining and Machine Learning at the University of Tennessee Health Science Center.
  15. Ph.D. position in Computer Vision in Engineering at Bauhaus University Weimar.
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