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Wednesday, April 12, 2017

K mean clustering sklearn best practice - Udacity Machine Learning Nanodegree Unsupervised Learning

There are three key k means clustering parameters in sklearn that you will need to pay attention to:

  • Number of centroids, aka center of clusters, initialized
  • Max number of iterations, used to optimize the algorithm. Best practice recommended by Udacity is 300
  • Number of different iterations, with initialization of centroids

Convert Tensorflow 1.0 to Tensorflow 2.0

Specify Tensorflow version in Google Colab `%tensorflow_version 2.x`. It is not recommended to use pip install in Google Colab: quote &quo...