print(score) [0.02676203621702298, 0.9923]
Convolution Extract info from the matrix by moving a filter/kernel arround the matrix,
Filters/Kernels Used to extract features from a matrix, should be odd sized to get the edges
Epochs Once we run the model through test data we call it one epoch
1x1 Convolution Taking a 1X1 matrix arround the input matrix and typically used to change the size of kernel
3x3 Convolution A 3X3 matrix is used to extra info and it is moved like a duster on the black board to extract info
Feature Maps A collection of all the points where our feature is present, collecting all Es from the image
Activation Function Used to decide the values of function, should be active or in-active based on the convluted data
Receptive Field In the next layer, how much info is present about pixels from the origional imageis called a recptive field, the last layer has global receptive field. And it should be atleast the size of the object