What is Natural Language Processing (NLP)? Natural Language Processing (NLP) is an area of Artificial Intelligence (AI) that focuses on computers understanding and processing human language. NLP helps machines understand the complexities of human language and enables them to ‘read’, interpret and make decisions based on the data they have processed. NLP is an important element of AI as it gives machines the ability to interact with humans in a natural way, allowing us to extend our capabilities beyond what was thought possible.

Introduction to Text Mining Text mining, also known as natural language processing (NLP), is an emerging field that has grown exponentially over the past decade. As data continues to become more abundant, text mining is becoming increasingly important for businesses and organizations in order to extract meaningful information from large amounts of unstructured text data. This blog post will provide an overview of the basics of text mining and discuss some of the most common techniques used to pre-process raw data, explore descriptive statistics, and apply machine learning algorithms.

Introduction to Natural Language Processing Natural language processing (NLP) is an area of computer science, artificial intelligence and computational linguistics concerned with the interactions between computers and human (natural) languages. It is used to help computers understand, interpret and manipulate natural language in order to process or generate information. NLP techniques are used in many areas including machine translation, automated question answering, text summarization, sentiment analysis and speech recognition.

Introduction to Text Mining and Natural Language Processing In the age of artificial intelligence and big data, text mining has become an increasingly important tool for uncovering insights from unstructured data. Text mining, also known as NLP (Natural Language Processing), is a powerful technique that enables organizations to gain deep understanding from large amounts of textual information. It can help identify patterns in the data, extract key words and phrases, and classify documents for automated knowledge discovery.