Perceptron, the simplest Neural Network.
I explain how it works.
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I explain how it works.
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The Perceptron is a binary classifier.
It can decide if data belongs to A or B or make yes or no decisions.
The two classes are usually represented with 0 and 1. I will use this notation in this thread.
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It can decide if data belongs to A or B or make yes or no decisions.
The two classes are usually represented with 0 and 1. I will use this notation in this thread.
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Here are the steps Perceptrons go through:
- It takes several inputs
- Apply weights and biases
- Provides output
If the result is less than or equal to 0, the output is 0.
If the result is higher than 0, the output is 1.
Let's see an example 🔽
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- It takes several inputs
- Apply weights and biases
- Provides output
If the result is less than or equal to 0, the output is 0.
If the result is higher than 0, the output is 1.
Let's see an example 🔽
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You want to decide whether to go to the cinema or not.
You have 3 factors:
- Weather
- Company
- Proximity
If the answer to a question is yes, then the input is 1, and 0 otherwise.
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You have 3 factors:
- Weather
- Company
- Proximity
If the answer to a question is yes, then the input is 1, and 0 otherwise.
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Let's add weights and biases
The most important thing for you is going with friends, so company gets a weight of 4. The other factors get 2.
Bias is -5
Note: This means that you must have friends to go with and at least one other factor.
Let's see why 🔽
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The most important thing for you is going with friends, so company gets a weight of 4. The other factors get 2.
Bias is -5
Note: This means that you must have friends to go with and at least one other factor.
Let's see why 🔽
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Consider this situation.
- Good weather
- No friends to go with
- No cinema nearby
According to the calculation below, you will not go to the cinema.
Remember if the result is negative, the output is 0 = No
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- Good weather
- No friends to go with
- No cinema nearby
According to the calculation below, you will not go to the cinema.
Remember if the result is negative, the output is 0 = No
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Now the situation changed:
- Still good weather
- Friends are available
- No cinema nearby
Since the result is positive, the output is 1 = Yes.
Now the only question is what movie to watch.
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- Still good weather
- Friends are available
- No cinema nearby
Since the result is positive, the output is 1 = Yes.
Now the only question is what movie to watch.
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That's it for today.
Check the video that inspired this thread:
youtu.be
I hope you've found this thread helpful.
Like/Retweet the first tweet below for support and follow @levikul09 for more Data Science threads.
Thanks 😉
8/9
Check the video that inspired this thread:
youtu.be
I hope you've found this thread helpful.
Like/Retweet the first tweet below for support and follow @levikul09 for more Data Science threads.
Thanks 😉
8/9
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