Deep Learning for NLP

Overview

Learn how to apply the latest innovative deep learning research and techniques to build genuinely state-of-the-art and next-generation natural language processing systems to further automate seamless contextual interactions between computers and humans.

Course Details

This course provides a hands-on and in-depth exploration of how deep learning techniques can be applied to build extraordinary natural language processing systems using the Python Keras deep learning API. This course follows on from our Applied Deep Learning course, and enables principal and lead data scientists to apply the latest cutting-edge deep learning research and techniques to build state-of-the-art natural language processing applications including the automatic generation of context-preserving text, speech recognition, and automatically generating text-based descriptions of images.

Course Modules

• 1. Long Short Term Memory
• 2. Word Embeddings
• 3. Generating Text
• 4. Speech Recognition
• 5. Deep Visual Semantics

Requirements

• Linear Algebra or equivalent.
• Statistical Learning or equivalent.
• Introduction to Deep Learning or equivalent.
• Applied Deep Learning or equivalent.

Outcomes

• The ability to apply the latest cutting-edge deep learning research and techniques in Python.
• The ability to build state-of-the-art next-generation natural language processing applications.
• Advanced knowledge of recurrent neural networks including long short term memory (LSTM) and gated recurrent units (GRU).