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Introduction to Machine Learning, a series of IPython Notebook and accompanying slideshow and video
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.gitignore
01_The_Dataset.ipynb
02_Clustering_KMeans.ipynb
03_Clustering_OtherAlgos.ipynb
04_Classification_kNN.ipynb
05_Classification_OtherAlgos.ipynb
06_Classification_Decision_Trees.ipynb
07_Classification_Random_Forest.ipynb
08_Dimensionality_Reduction.ipynb
LICENSE
README.md
fruit.csv

README.md

Introduction to Machine Learning

a series of IPython Notebook and accompanying slideshow and video

Link to accompanying reveal.js slideshow

Link to PDF version of slideshow

Link to video presentation I'm so sorry, my google account was hacked and although I was able to get my gmail and OAuth back, all my youtube videos including this one with > 100,000 views, were permanently erased.

IPython notebooks:

  1. The Dataset
  2. Clustering with K-means
  3. Clustering with other algorithms
  4. Classification with k-Nearest Neighbors
  5. Classification with other algorithms
  6. Classification with Decision Trees
  7. Classification with Random Forests
  8. Dimensionality reduction
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