Decoding CNN layer is interesting concept and quite easy to understand.
Let’s try to understand it example of image. Let’s see what happens if our input data is a image which is 2-dimensional.
In a layer, each pixel (eg. in CNN layer 1)represent receptive field (eg. in Input layer ) from previous layer.
We are considering Stride (s) = 2 w.r.t row and column. Height and Width of receptive field is also same denoted by f = 3.
Now I want to check in CNN layer 1 that first pixel belongs to which receptive field in input layer. …
Stemming and Lemmatization are steps to convert a word into root form. The root form of word we get from Stemming and Lemmatization are called “Stem” and “Lemma”, respectively. The difference between stemming and lemmatization is that stem might be meaningful or meaningless word but lemma will always be meaningful word.