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Deep learning introduction

Deep learning was a subset of machine learning and inspired by human neural system.

We take an example we see car it was as first captured by our eyes then inside neurones transfer this information to our brain their it analyses what object it was then finally based on our brain prediction, we come a conclusion it was car or not.

Now we understand deep learning also working on the same process neural networks.

Here we have mainly three layers been there

1.input layer

2.hidden layer

3.output layer

Input layer we pass all our features to hidden layers along with some weights and bias.

I going to explain in-depth about weights, bias, activation function, loss function in my coming blogs, here I am giving introduction to the neural networks.

In hidden layer weights and features are multiplied and the formula is

Then hidden layer to output layer process will be happening.

Here new weights and hidden layer values are multiplied and the formula

In out put layer activation function will predict either car or not in our example, here I am suppose using sigmoid function and the formula was

sigmoid function formula

thank you for reading in my coming stories I am going to explain in-depth about these formulas and terminologies..

AI/ML

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