NVIDIA DLI Workshop - Wednesday 18 September 2019
Fundamentals of Deep Learning for Natural Language Processing
|Date & Time||Venue||Price|
Wednesday 18 September 2019
8.30am - 5.30pm
4-12 Norton Folgate
London E1 6DQ
£795 + VAT
Group discount of 20% for 3 or more places
(Discount automatically applied at checkout)
This workshop teaches deep learning techniques for understanding textual input using natural language processing (NLP) through a series of hands-on exercises. You will 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. New techniques like BERT will also be presented during the workshop.
Modern deep learning frameworks have transformed speech recognition and Natural Language Processing (NLP), and have seen an increase in financial applications for alpha generation and risk management.
New language models, such as BERT, allow for a much deeper understanding of context than than the traditional NLP models. When mining the news, corporate and regulatory filings, or social media for trading signals, we are now able to get much better signal-to-noise ratios than when using the traditional sentiment analysis or named entity recognition (NER) tools. This in turn can inform a better understanding of counterparty default risks, geopolitical risks, or even exchange rate risks, allowing for better decision making and hedging.
At the conclusion of the workshop, you’ll have an understanding of:
- Classical approaches to convert text to a machine-understandable representation
- Implementation and properties of distributed representations (embeddings)
- Methods to train machine translators from one language to another
Yuval Mazor is a Senior Solutions Architect with NVIDIA, helping customers and partners succeed with their Deep Learning endeavors. He has 20 years of industry experience as a developer, architect and technical leader in algorithms, software design and implementation and machine/deep learning. He has worked in diverse environments, ranging from 2-person startups to large multi-nations. Yuval is passionate about technology and its implications to daily life – as such he speaks often in user groups and conferences. Yuval has a Bachelor’s degree in Computer Science and has done graduate work in Computational Linguistics and Natural Language Processing at Tel Aviv University.
PLEASE BRING YOUR OWN LAPTOP, NO SPECIAL SOFTWARE OR HARDWARE REQUIRED.