Text Processing using Machine Learning

The landscape of Natural Language Processing (NLP) has undergone a significant transformation since the emergence of

Deep Learning and Large Language Models.Deep Learning, a subfield of machine learning, has revolutionised NLP by enabling models to learn and understand language patterns and structures more effectively, leading to advancements in various NLP tasks such as semantic parsing, sentiment analysis, machine translation, and question-answering systems. The development of Large Language Models, such as OpenAI's GPT-3, has further propelled NLP capabilities by training models on massive amounts of data, enabling them to generate coherent and contextually relevant text. These models have shown remarkable proficiency in language understanding, text generation, and even performing creative writing tasks.

The combination of Deep Learning and Large Language Models has not only propelled the field towards more sophisticated and powerful language processing capabilities but has also opened up new possibilities for applications in fields like healthcare, customer service, and language translation.

This course is designed to meet the pressing demand for expertise in cutting-edge language technologies. From classic DNN models to the revolutionary Transformer architecture, from transfer learning to Large Language Models (LLMs), this course demystifies the complexities of language processing and the intricacies of deep learning, ensuring you're equipped to meet the demands of the data-driven future to harness the transformative power of Generative AI (GenAI).