What is encoding and decoding in NLP?

This recipe explains what is encoding and decoding in NLP

Recipe Objective

What is encoding and decoding in NLp?

Encoding and Decoding comes under sequence to sequence modeling which is nothing but aims to map a fixed-length input with a fixed-length output where the length of input and output may differ. Encoder The stack of various recurrent units where LSTM or GRU cells are for better performance in which each accepts one single element of the input sequence, the information collection is done for that element and communicating it forward. The input sequence is a collection of all words from the question in question answering problem. The representation of each word is done as x_i in which i is the order of that word. Decoder It is a stack of several recurrent units where each predicts an output at a time step. The output as well as the own hidden state is produced when each recurrent unit accepts a hidden state from the previous unit. The output sequence is a collection of all the words from the answer in case of question and answering problem whereas the representation of each word is as y_i in which i is the order of that word.

NLP Techniques to Learn for your Next NLP Project

Step 1 - Take a sample string

Sample_string = 'This is a Sample text'

Step 2 - Print the Sample string

print('The Sample string is:', Sample_string)

The Sample string is: This is a Sample text

Step 3 - Encode the Sample string

Sample_encode = Sample_string.encode() By default the string gets encoded in "utf-8"

Step 4 - Decode the encoded string

Sample_decode = Sample_encode.decode()

Step 5 - Print the results

print('The encoded string is:', Sample_encode, '\n') print('The decoded string is:', Sample_decode)

The encoded string is: b'This is a Sample text' 

The decoded string is: This is a Sample text

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