K-Nearest-Neighbors-with-Dynamic-Time-Warping

markdregan

Python implementation of KNN and DTW classification algorithm

machine-learning

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636 Stars

203 Forks

636 Watchers

Jupyter Notebook Language

Cost to Build

$555.3K

Market Value

$1.36M

How is this calculated?

Growth over time

1 data points · 2021-08-07 → 2021-08-07

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What is the markdregan/K-Nearest-Neighbors-with-Dynamic-Time-Warping GitHub project? Description: "Python implementation of KNN and DTW classification algorithm". Written in Jupyter Notebook. Explain what it does, its main use cases, key features, and who would benefit from using it.

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