Introduction to Natural Language Processing
A technique called Natural Language Processing (NLP) focuses on comprehending human language in the field of artificial intelligence.
We can develop a model to comprehend language rooted in human language using programming methods. This model can classify content and generate and compose new compositions. The intricacies of these techniques will be explored in forthcoming article. The main focus of this book is on the fundamental concepts and techniques for modelling language and training neural networks to understand and classify text. A machine learning model’s predictive nature can be used not only for amusement but also to craft poetry, as well. This article examines how language is broken down into numerical representations and how these numerical representations can be used within neural networks to understand language.
For representing language numerically, there are various methods. When you store strings in your code, most encodings use letters. In memory, letters are not directly stored. It is instead encoded as ASCII or Unicode. As an example, take the word “listen.”. This number has 76, 73, 83, 84, 69, and 78 ASCII characters. The word now can be expressed using numeric values, which has its advantages. Take the word “silent,” which is opposite to “listen.” Although the numbers represent the same word, they are arranged differently, making it difficult to construct a model for text understanding.