Implementing Gaussian Naive Bayes from Scratch

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In this video, we implement Gaussian Naive Bayes model from scratch.

#ai #softwareengineering #programming #stylepoint #naivebayes

Chapters
0:00 - Intro
0:40 - Thinking about the API
1:35 - Implementing the `fit` method
5:14 - Implementing the `predict` method
9:37 - Testing
9:57 - Outro
  1. David Oniani
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Комментарии
Автор

two comments:
1: the api is unusual - there is no need to save the training data on the instance, those should be args to `.fit` rather that `__init__`
2: it's numerically more stable to use log-likelihoods (and sums instead of products)

grosucelmic
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I have added the timestamps for the video.
Hope this will be helpful (:

davidoniani
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This was really well done. Straight to the point but still elaborating on details people may have forgotten. My one suggestion: before testing the full dataset, it would've been nice to step through the finished code with a toy dataset and see the result of each step. Jumping right into performance metrics made the end seem greater than the sum of its parts

whaley
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Really enjoyed the video, nice work!
Perhaps in the description it would be useful to include a link to a good quality source for those hoping to understand the underlying theory of the algorithm in more depth.

joshwapiano