Artificial Intelligence in NLP
Dhanalekshmi Prasad Yedurkar, Ganesh Rajaram Pathak, Manisha Galphade, Thompson Stephan · 2025
Machine Learning (ML) has revolutionized Natural Language Processing (NLP) by enabling intelligent language understanding and generation. This chapter explores fundamental ML techniques, including supervised and unsupervised learning, and their applications in processing natural language sentences. Hybrid machine learning systems, which combine multiple approaches for improved NLP performance, are also discussed. The study introduces deep learning in NLP, highlighting its ability to model complex linguistic structures through neural networks. Various NLP applications, such as sentiment analysis and next-word prediction, are examined to demonstrate the impact of ML-driven language models. These techniques enhance real-world applications, including chatbots, machine translation, and text generation. By analyzing these ML methodologies and their role in NLP, this study provides insights into how advanced learning models contribute to more accurate and context-aware language processing, driving innovations in artificial intelligence and human-computer interaction.