Fundamentals of Deep Learning for Natural Language Processing
Presented by SGInnovate, NVIDIA & NSCC
Learn to implement common Deep Learning workflows such as image segmentation and text generation. You should also have basic experience with Neural Networks, Python programming and / or familiarity with linguistics.
Led by experienced instructors, you can expect to learn the latest deep learning techniques for designing and deploying neural network-powered machine learning across a variety of application domains.
In the course, participants will learn to:
- Convert text to representation understood by machines and classical approaches
- Implement distributed representations (embeddings) and understand their properties
- Train Machine Translators from one language to another
This workshop teaches you to apply deep learning techniques for understanding textual input using Natural Language Processing (NLP) through a series of hands-on exercises. You will work with widely-used deep learning tools, frameworks, and workflows by performing neural network training on a fully-configured GPU accelerated workstation in the cloud.
The course starts with the technique of training a neural network for text classification followed by building a linguistic style model to extract features from a given text document and concludes with a neural machine translation model for translating one language to another.
You should also have basic experience with Neural Networks and python programming and/or familiarity with linguistics.
Click here for more SGInnovate – NVIDIA Training Programmes.
08:45am – 09:00am: Registration
09:00am – 09:45am: Introduction
Introduction to deep learning, situations in which it is useful, key terminology, industry trends and challenges
- Course Overview
- Getting Started with Deep Learning
09:45am – 10:00am: Tea Break
10:00am – 12:00pm: Image Segmentation with TensorFlow
Hands-on exercise: Segment MRI images to measure parts of the heart using tools such as TensorBoard and the TensorFlow Python API
- Compare image segmentation to other computer vision problems
- Experiment with TensorFlow tools
- Implement effective metrics for assessing model performance
12:00pm – 1:00pm: Lunch
1:00pm – 3:00pm: Word Generation with TensorFlow
Hands-on exercise: Train a Recurrent Neural Network to understand both images and text, and to predict the next word of a sentence using the MSCOCO (Microsoft Common Objects in Context) dataset
- Introduction to Natural Language Processing (NLP) and Recurrent Neural Networks (RNNs)
- Create network inputs from text data
- Test with new data
- Iterate to improve performance
3:00pm – 3:15pm: Tea Break
3:15pm – 5:15pm: Image and Video Captioning
Hands-on exercise: Train a model that generates a description of an image from raw pixel data by combining outputs of multiple networks (CNNs and RNNs) through concatenation and/or averaging.
- Combine computer vision and natural language processing to describe scenes
- Learn to harness the functionality of Convolutional Neural Networks (CNNs) and RNNs
5:15pm – 5:30pm: Summary
Review of concepts and practical takeaways
- Summary of key learnings
- Workshop survey
- Regular Ticket: SGD$450 / pax (before GST)
- 5% Early Bird Discount (ends 28 April 2019) - SGD$427.50 / pax (before GST)
- 10% Bundle Discount when your purchase together with Fundamentals of Deep Learning for Multiple Data Types Workshop (ends 14 May 2019) - SGD$810 / pax (before GST)
For group discounts or enquiries, please contact [email protected].
Timothy is a certified NVIDIA DLI instructor for the Fundamentals of Natural Language Processing workshop. He is also an NVIDIA University Ambassador for the Singapore University of Technology and Design (SUTD). He is experienced in conducting workshops on Deep Learning and is also involved in a variety of projects such as machine intelligence, cybersecurity and cloud infrastructure. He is currently pursuing his Bachelor’s degree at SUTD while interning at the NVIDIA AI Technology Centre.