Deep Learning

 This layer is used to downsample the shape of an image Suppose you have an image- [ 2 3 4 5   3 4 5 6   4 5 6 7 ] if pool size is (2,2) then output will [ 4 6   5 7 ]

This is the main layer of feature extraction part of the convolution neural networks. Convolution layer They had a filter of shape (x,x), generally x=3 so shape of filter is (3,3). Kernel 2 2 1 3 3 3 3 2 1 Image 2 3 5 3 3 3  (2*2)+(3*2)+(5*1)+(3*3)+(3*3)+(3*3)+(3*3)+(2*2)+(1*1)=56 3 2 1 Every pixel will change by 56 of image

 CNN(Convolution Neural Network) CNN is used to classify images CNN is most effective for 2D data CNN has three layers-: 1> Convolution layer for extracting feature 2> Max Pooling layer for reducing dimension 3> Flatten for Convert 2D to 1D because we have to pass to ANN prediction 4> Next ANN Network

How to train a neural network for training regression model?  In previous class we discus about to train multiclass classification to convert it to regression model we have to just change last neuron to single perceptron 

 How to train a neural network for multiclass classification?  In previous class  we learnt about to Binary Classification  in neural network to change it to multiclass classification we do S1 S1="In neural network we have to just change the last neuron units to no.classes"

 How to train a neural network  for Binary classification ? 1. Install anaconda 2. Open jupyter notebook 3. Create file called app.py 4. Click Here to See Code