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PyConEs 2019
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notes.md

PyconES, notes

Lots of people!

Keynote Safia

  • You are the average of the 5 people you spent most the time with
  • Conway law (organization structure)
  • Like code ideas

Mom, I want to be a data artist

  • Copying and following inspiring people

assertTrue('Testing en Machine Learning')

  • Tests específicos para datos y modelo
  • En cada step de la pipeline: procesar datos, definir modelo, entrenar.
  • Procesamiento: detectar nulos, cadenas vacías, out-of-range, imagenes mal, correlaciones entre feature-labels, valores duplicados, balanceo de clases, distribución de los splits, distribuciones en series temporales.
  • Definir modelo: sobreentrenar modelo, introducir info artificial, suffle de datos
  • https://pycones19.sched.com/event/37b2c7328b8516576eba750c442a9974

Que la generación Z no rompa tus modelos

  • Bias en ML

DDD approach to Nameko microservices

Flow is in the air

¿Cómo preparar una prueba técnica?

  • Cuestiones controlables vs incontrolables
  • Cultural fit = tech culture
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