Notes on Sigmoid Neuron (PadhAI onefourthlabs course “A First Course on Deep Learning”)

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Notes on Sigmoid Neuron (PadhAI onefourthlabs course “A First Course on Deep Learning”)

Perceptron model fails when we have non linearly separable data like this
Sigmoid neuron in 3-D space
If we have data like this which is non-linearly separable as in fig(1) and the green points are surrounded by red points as in fig(2) its very difficult to classify and perceptron model classifies at max level as shown n fig(3)
Refer this for the above notes…
Like this we can classify data
We can classify differently and more accurately compared to Percpetron

This is a small try ,uploading the notes .I believe in “Sharing knowledge is that best way of developing skills”. This is the notes of “ Sigmod Neuron” part of the course.Mathematical part of the sigmoid neuron will be published Soon.Comments will be appreciated.Even small edits can be suggested.

Each Applause will be a great encouragement.

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