#38: Scikit-learn 35:Supervised Learning 13: Orthogonal Matching Pursuit

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The video discusses the implementation of Orthogonal Matching Pursuit algorithm in Scikit-learn in Python using an example of noisy signal reconstruction.

Timeline
(Python 3.8)

00:00 - Outline of video
00:27 - Open Jupyter notebook
01:00 - Create signal data using .make_sparse_coded_signal()
05:50 - Create noise data
06:39 - Get indicies of non-zero elements in sparse array
07:26 - Plot: raw signal
09:00 - OrthogonalMatchingPursuit(): Noise free reconstruction
10:33 - Plot: Noise free reconstruction
12:38 - OrthogonalMatchingPursuit(): Noisy data reconstruction
13:28 - Plot: Noisy data reconstruction
14:08 - OrthogonalMatchingPursuit(): Noisy data reconstruction using CV (cross validation)
15:05 - Plot: Noisy data reconstruction using CV
15:25 - Ending notes
  1. learndataa
  2. orthogonal matching pursuit
  3. linear model
  4. supervised machine learning
  5. linear models
  6. Scikit-learn tutorial
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