A Brief Introduction to Natural Language Processing (Part II)

2 min readSep 15, 2019

What is Natural Language Processing (a.k.a) NLP?

We all know that computers can only understand machine language which contains a string 0’s and 1’s ie Binary numbers. Have you ever wondered how to make it understand human language? Natural Language Processing is a way to teach computers to understand human language and process it to give a useful output. Using Natural Language Processing, now we can speak/text with computers as we normally do with other human beings and expect a meaningful reply back. This is the evolution of Natural Language Processing over the years.

Applications of Natural Language Processing:

Natural Language processing is everywhere now. Few of the applications are:

Google Assistant, Siri, Bixby in Mobile Devices
Chatbots
Gmail mail reply suggestions
Predictive Text
Data classification

The above are a few of the applications of Natural Language Processing.

Algorithms Used in Natural Language Processing:

Natural Language Processing mostly uses classification algorithms. Algorithms which can be used for Natural Language Processing are:

Naive Bayes
Maximum entropy classifier
Decision Tree
Random Forest
XGBoost
Support Vector Machine
Multi-layer perceptron
LSTM

Decision Trees:

Decision Trees are simple classifiers which use the data to make a visualizable tree and fit the data in it. Tree-based algorithms are considered to be one of the best algorithms for the classification of data and are most commonly used supervised learning technique. Unlike linear models, they map non-linear relationships quite well. They are adaptable at solving any kind of problem at hand (classification or regression).

References:

AnalyticsVidhya
Medium
Expert System