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Exploration and data curation of a dataset given by a Kaggle competition (https://www.kaggle.com/dansbecker/melbourne-housing-snapshot) related to properties that were sold in Melbourne in 2016 and 2017. The meaning of this project is to prepare a well-structured matrix, so it can be used to run a model in order to estimate their prices.

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melbourne properties price estimation machinelearning datacuration exploration

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Exercise 3: PCA

  1. Aplique PCA para obtener n componentes principales de la matriz, donde n = min(20, X.shape[0]). ¿Es necesario estandarizar o escalar los datos?

Exercise 3: Variance

  1. Grafique la varianza capturada por los primeros n componentes principales, para cada n.
  2. En base al gráfico, seleccione las primeras m columnas de la matriz transformada para agregar como nuevas características al conjunto de datos.

Exercise 5: Documentation

En un documento .pdf o .md realizar un reporte de las operaciones que realizaron para obtener el conjunto de datos final. Se debe incluir:

  1. Criterios de exclusión (o inclusión) de filas
  2. Interpretación de las columnas presentes
  3. Todas las transofrmaciones realizadas

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