Best links of the week #18

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Best links of the week from 6th May to 12th May

Source: xkcd.

Links

  1. NextJournal, Seamless Data Science for Teams.
  2. An executive’s guide to AI.
  3. What should I use to serve R applications over the internet? at Brian Caffo’s YouTube channel. He talks about PlumbeR (PlumbeR book here).
  4. Will AI eat statistics? at Brian Caffo’s YouTube channel.
  5. A radical new neural network design could overcome big challenges in AI at MIT Technology Review.
  6. Urgent need for a government-led big data system, say industry experts at The Edge Markets.
  7. Top 10 Cities Across The Globe With The Highest Pay Packages For Data Scientists at Analytics India.
  8. What Nobody Tells You About Machine Learning at Forbes.
  9. How the data mining of failure could teach us the secrets of success at MIT Technology Review.
  10. How to hide from the AI surveillance state with a color printout at MIT Technology Review.
  11. Boosting (machine learning) at Wikipedia.
  12. Weak Learning, Boosting, and the AdaBoost algorithm at Jeremy Kun’s Blog.
  13. Weak vs. Strong Learning and the Adaboost Algorithm at Jenn Wortman Vaughan’s Website.
  14. What is a weak learner? at StackOverflow.
  15. AI está pronta para transformar radicalmente o desenvolvimento de software at CIO.
  16. O orçamento das universidades e institutos federais desde 2000 at NexoJornal.
  17. O governo contra as universidades, em dados e análises at NexoJornal.
  18. Existe alguma microevolução documentada nos humanos nos últimos duzentos anos? at Quora.

Blog/posts

  1. Pearl’s Causal Ladder at Smitha Milli’s Blog.
  2. Artificial Intelligence — The Revolution Hasn’t Happened Yet at Michael Jordan Medium.
  3. A Gentle Introduction to Transfer Learning for Deep Learning at Machine Learning Mastery.
  4. Transfer learning at Wikipedia.
  5. The Four Cs of Data + Design at Ben Fry’s Medium.
  6. Winning Solution of KaggleDays 2019 Competition in San Francisco at Mark Peng’s LinkedIn.
  7. What is One Hot Encoding? Why And When do you have to use it? at Hackernoon.
  8. Cross-Validation for Predictive Analytics using R at MilanoR.
  9. O que faz um Engenheiro de Dados? by Allan Sene at Data Hackers’ Medium.
  10. Os Tipos de Engenheiros de Dados by Allan Sene at Data Hackers’ Medium.

Videos

  1. Cross Validation in R | Arpan Gupta | Data Scientist & IITian at Data Science by Arpan Gupta IIT,Roorkee.
  2. Introduction to Data Science with R – Cross Validation at David Langer YouTube channel.

Scientific Article

  1. On Weak Learning at Journal of Computer and System Sciences.
  2. Quantifying dynamics of failure across science, startups, and security at arXiv.org.

Podcasts

  1. Episódio 020: Estatística e Machine Learning at Pizza de Dados.

Positions available

  1. Estágio em Inteligência Artificial at docket.
  2. Engenheiro de dados at B2W Digital.
  3. Professor(a) plataformas Cloud at Alura.
  4. Analista de Business Intelligence at Youse.
  5. Engenharia de Dados at petlove.
  6. Several opportunities at Science Me Up!
  7. Analista de Banco de Dados at RecrutaSimples.
  8. Consultor BI/Big Data/Analytics at RedFox Soluções Digitais.
  9. Estágio – BIG Data/Analytics at RedFox Soluções Digitais.
  10. Analista de Dados (Business Intelligence) at INSIDE SALES.
  11. Cientista de Dados at Yellow Rec.
  12. Analista de Business Intelligence at Gente e Gestão & Projetos.
  13. Several data positions at Farfetch.
  14. Analista de Dados (Business Intelligence) at Stone Pagamentos.
  15. Arquiteto de Soluções Cloud at Hitss do Brasil Serviços Tecnológicos LTDA.
  16. Analista BI (foco em dados) at ENJOEI.
  17. Estágio em Engenharia de Dados at Data Sprints.
  18. Profissional de Engenharia de Dados (Data Engineer) at Magnetis.
  19. Open PhD call 2019 – Italian Institute of Technology (Pattern Analysis & Computer Vision – PAVIS & Visual Geometry and Modeling Lab – VGM Lab) and University of Genova, Italy.
  20. 3 year PhD position in Deep Learning for Text Analytics @ U Essex.
  21. 3-year position on Text Analytics & Image Processing for Post-doc/Pre-doctoral researcher in London (KTP – Innovate UK).
  22. PhD openings in machine learning and artificial intelligence for UAV communications and tracking (here and here).
  23. PhD in Biomedical Information Extraction, The University of Manchester.
  24. Funded PhD position on Behaviour-Driven Optimisation of Neural Connectivity at the University of Plymouth, UK.
  25. Two postdoctoral research positions on Data Science at the University of Exeter.