Natural language processing (NLP) is a widely discussed and studied subject these days. NLP, one of the oldest areas of machine learning research, is used in major fields such as machine translation speech recognition and word processing. In this article, I’ll walk you through 20 Machine Learning projects on NLP solved and explained with the Python programming language.
20 Machine Learning Projects on NLP
- Resume Screening with Python
- Named Entity Recognition with Python
- Sentiment Analysis with Python
- Keyword Extraction with Python
- Spelling Correction Model with Python
- Keyboard Autocorrection Model
- Election Results Prediction by analyzing Tweets
- NLP for Other languages
- Text Classification using Deep Learning
- Summarize Text with Machine Learning
- Hate Speech Detection Model
- Keyword Research with Python
- Whatsapp Group Chat Analysis
- Next Word Prediction Model
- Fake News detection Model
- NLP for Whatsapp Chats
- Twitter Sentiment Analysis
- SMS Spam Detection Model
- Movie Reviews Sentiment analysis
- Amazon Product Reviews Sentiment Analysis
How Natural Language Processing Works?
Natural language processing is an integral area of computing in which machine learning and computational linguistics are widely used. This area mainly aims to make human and computer interaction easy but efficient.
The machine learns the syntax and meaning of human language, processes it and gives the output to the user. The field of NLP involves creating computer systems to perform meaningful tasks with natural language understandable to humans.
The reason why natural language processing is so important in the future is that it helps us build models and processes that take chunks of information as input and as voice or text or both and manipulate them according to the algorithm inside the computer.
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