What is the K-Nearest Neighbor (KNN) Algorithm?

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Join Martin Keen as he provides an in-depth explanation of the K-Nearest Neighbors (KNN) algorithm, a popular classification and regression classifier in machine learning. Martin covers the basics of KNN, including its assumption that similar data points are located near each other, and how it works with examples - as well as the strengths and weaknesses of KNN, including its simplicity, adaptability, and scalability issues.

  1. IBM Technology
  2. IBM
  3. IBM Cloud
  4. K-Nearest Neighbors
  5. KNN
  6. Classification
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Комментарии
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Let's all take a moment to appreciate how cool the glowing marker ink is

blehbleheh
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I never noticed it. Board reflecting tele prompter.

captainoddessy
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It's amazing and wonderful to see such content

instantshortsmotive.
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Excellent! Can you also explain the random forest algorithm?

vdpoortensamyn
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thank you. i am starting a journey to learn AI. I accidentally found this channel!
If you are a begginer like me, you are on a right channel

engineerfiks
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My professor did not explain this this well, thank you so much! 😅

tesm_jsf
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Can you switch to a light theme? It's so bleak watching a guy in a black roomtalking about algorithms.

severalpens
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Thank you Martin, for the explanation of KNN algorithm and its benefits and disadvantages, it was insightful!

samsonv
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Interesting thank you. So whats better than KNN?

RadiantNij