Natural Language Processing – Sentiment Analysis using LSTM
Introduction:
This article aims to explain the concepts of Natural Language Processing and how to build a model using LSTM (Long Short Term Memory), a deep learning algorithm for performing sentiment analysis. Let’s first discuss Natural Language processing!
Natural Language Processing:
Natural Language Processing (NLP) is a subfield of Artificial Intelligence that deals with understanding and deriving insights from human languages such as text and speech. Some of the common applications of NLP are Sentiment analysis, Chatbots, Language translation, voice assistance, speech recognition, etc.
Few Real-time examples:
- Google translator
- Chatbots in Apps like Flipkart & Swiggy
- Autocompletion feature in Gmail
- Personal Assistance like Alexa, Siri & Google Assistance
- Email spam detection
- Document summarization
Importance of NLP:
Why is it necessary to know about NLP? The reason for this is that in today’s world, roughly 2.5 quintillion bytes of data are generated every day. And the majority of them are inherently unstructured. Examples: Text, audio, etc. To