Description
Natural language processing (NLP) is a field of artificial intelligence (AI) machine learning and computational linguistics.
During the course, you’ll learn how NLP is one of the most important technologies of the Information Age. You’ll gain a deeper understanding of this aspect of AI by delving into its sub areas including; natural language understanding, machine translation, semantics, and syntactic passing as well as natural language emulation and dialectal systems.
Requirements
- Introduction to NLP and Deep Learning provides an overview of Natural Language Processing using classic machine learning methods and cutting-edge deep learning methods.
- Neural models for machine translation and conversation gives an introduction to Statistical Machine Translation and neural models for translation and conversation.
- Deep Semantic Similarity Models (DSSM) gives an introduction to Deep Semantic Similarity Model (DSSM) and its applications.
- Natural Language Understanding gives an introduction to methods applied in Natural Language Understanding, such as continuous word representations and neural knowledge base embedding.
- Deep reinforcement learning in NLP gives an introduction to deep reinforcement learning techniques applied in NLP.
- Vision-Language Multimodal Intelligence gives an introduction to neural models applied in Image captioning and visual question answering