Text Processing using Machine Learning

In the field of natural language processing (NLP), deep learning techniques have taken a dominant position over tradition statistical methods. Researchers have been reporting much higher performance metrics applying deep learning to solve problems like text classification, language modeling, speech recognition, caption generation, machine translation, document summarisation, question answering, etc. This course provides essential knowledge and skills required to perform deep learning based text processing in common tasks encountered in industries. A combination of lectures, case studies, and workshops will be used to cover the application of DL techniques such as word-embedding, Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), LSTMs, character-based language modelling, encoder-decoder models, reinforcement learning, etc. This course is part of the Artificial Intelligence, Data Science and Graduate Certificate in Practical Language Processing Series offered by NUS-ISS.