Penguins 13. Normalize features | End to End Machine Learning

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221. The k-nearest neighbors algorithm

Penguins

Penguins Intro (4:35)
Penguins 0. Read in the penguins data file (3:42)
Penguins 1. Break out each line into its fields (3:28)
Penguins 2. Convert numerical fields to floats (3:41)
Penguins 3. Handle NAs in the numerical fields (2:40)
Penguins 4. Convert sex field to a number (3:05)
Penguins 5. Handle NAs in the sex field (2:26)
Penguins 6. Convert penguin species to a numerical code (1:49)
Penguins 7. Populate feature and label arrays (7:43)
Penguins 8. Divide the penguins up into training and testing groups
Penguins 9. Randomly sort penguins into training and testing groups (5:24)
How k-nearest neighbors works (26:19)
Penguins 10. Find the nearest neighbors (6:42)
Penguins 11. Find the predicted species and tally the score (5:55)
Penguins 12. Account for ties (3:41)
Penguins 13. Normalize features (7:01)
Penguins 14. Monte Carlo cross validation (5:57)
Penguins 15. Adjust train/test split (3:31)

Penguins 13. Normalize features

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