Enlaces semana 2016 #33

  • Machine Learning meets ketosis how to effectively lose weight: Early in the process I figured I could use machine learning to identify the factors that made me gain or lose weight. I used a simple method: every morning I would weigh myself, and record both the new weights and whatever I did in the past ~24 hours, not just the food I ate, but also whether I exercised, slept too little or too much, etc. .
  • Document Classification with scikit-learn : Document classification is a fundamental machine learning task. It is used for all kinds of applications, like filtering spam, routing support request to the right support rep, language detection, genre classification, sentiment analysis, and many more. To demonstrate text classification with scikit-learn, we’re going to build a simple spam filter. While the filters in production for services like Gmail are vastly more sophisticated, the model we’ll have by the end of this tutorial is effective, and surprisingly accurate. .
  • PEP 526 — Syntax for Variable and Attribute Annotations Python.org: a python siguen intentando agregar funcionalidad de tipado. La falta de tipado estático  sea una gran virtud, pero a la vez su mayor defecto.
  • progressbar 2.3 Python Package Index: Grandes librerías de ayer y hoy para python. Esta es una de tantas barras de progreso para consola.
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