活動內容
Fundamentals of Deep Learning for Natural Language Processing
This workshop teaches deep learning techniques for understanding textual input using natural language processing (NLP) through a series of hands-on exercises. You’ll learn techniques to train a neural network for text classification, build a linguistic style model to extract features from a given text document, and create a neural machine translation model for converting text from one language to another.
Learning Objectives
At the conclusion of the workshop, you’ll have an understanding of:
1. Classical approaches to convert text to a machine-understandable representation
2. Implementation and properties of distributed representations (embeddings)
3. Methods to train machine translators from one language to another