ECE 595ML Lecture 17.1: Perceptron - Perceptron Algorithm

By Stanley H. Chan

Electrical and Computer Engineering, Purdue University, West Lafayette, IN

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Researchers should cite this work as follows:

  • Stanley H. Chan (2020), "ECE 595ML Lecture 17.1: Perceptron - Perceptron Algorithm," https://nanohub.org/resources/32601.

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WTHR 200, Purdue University, West Lafayette, IN

ECE 595ML Lecture 17.1: Perceptron - Perceptron Algorithm
  • Lecture 17.1: Perceptron - Perceptron Algorithm 1. Lecture 17.1: Perceptron - Per… 0
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  • Overview 2. Overview 40.407073740407078
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  • Outline 3. Outline 68.301634968301641
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  • Perceptron with Hard Loss 4. Perceptron with Hard Loss 250.01668335001671
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  • Re-defining the Loss 5. Re-defining the Loss 407.14047380714049
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  • Equivalent Perceptron Loss 6. Equivalent Perceptron Loss 521.021021021021
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  • Equivalent Perceptron Loss 7. Equivalent Perceptron Loss 719.18585251918591
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  • Equivalent Perceptron Loss 8. Equivalent Perceptron Loss 722.68935602268937
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  • Equivalent Perceptron Loss 9. Equivalent Perceptron Loss 724.4577911244578
    00:00/00:00
  • Equivalent Perceptron Loss 10. Equivalent Perceptron Loss 726.22622622622623
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  • Perceptron Algorithm 11. Perceptron Algorithm 778.11144477811149
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  • Perceptron Algorithm 12. Perceptron Algorithm 929.82982982982992
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  • Perceptron Algorithm 13. Perceptron Algorithm 1068.0347013680348
    00:00/00:00
  • Updating One Sample 14. Updating One Sample 1132.9662996329664
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