SG HEALTHCARE AI
DATATHON & EXPO
Sponsored by NSCC
30 November 2021
10am - 6pm (GMT+8)
in Collaboration with NSCC
13 July 2021
9am - 5pm
Registration $25 (incl processing fee)
Registration is now open! Only 40 seats left!
Program and registration details coming soon!
Monday, 7 December 2020
Full Day (9-5pm)
Webinar link to be sent out after registration is confirmed
Details of the workshop will be out shortly!
Nvidia - One API Hands-on Workshop
Date: 10 July 2021
Time: 9am - 5pm
Registration details coming soon.
This workshop is for Computer Vision developers, data scientist or software developers who are interested to know what is is OpenVino™ Toolkit and learn how to use it in accelerate and deployment on Intel® platforms. or interested to know how to kick start develop analytic project and optimize classic computer vision applications built with the OpenCV library or OpenVX API and harness the performance of Intel ® -based accelerators.
At the end of the workshop, participants will be able to:
NVIDIA DEEP LEARNING INSTITUTE IN COLLABORATION WITH NSCC
Building Transformer-Based Natural Language Processing Applications
Workshop Information and Prerequisites:
Duration: 8 hours
But please check out our other exciting workshops, Thanks!
Applications for natural language processing (NLP) have exploded in the past decade. With the proliferation of AI assistants and organizations infusing their businesses with more interactive human-machine experiences, understanding how NLP techniques can be used to manipulate, analyze, and generate textbased data is essential. Modern techniques can capture the nuance, context, and sophistication of language, just as humans do. And when designed correctly, developers can use these techniques to build powerful NLP applications that provide natural and seamless human-computer interactions within chatbots, AI voice agents, and more.
Deep learning models have gained widespread popularity for NLP because of their ability to accurately generalize over a range of contexts and languages. Transformer-based models, such as Bidirectional Encoder Representations from Transformers (BERT), have revolutionized NLP by offering accuracy comparable to human baselines on benchmarks like SQuAD for question-answer, entity recognition, intent recognition, sentiment analysis, and more.
In this workshop, you’ll learn how to use Transformer-based natural language processing models for text classification tasks, such as categorizing documents. You’ll also learn how to leverage Transformer-based models for named-entity recognition (NER) tasks and how to analyze various model features, constraints, and characteristics to determine which model is best suited for a particular use case based on metrics, domain specificity, and available resources.
By participating in this workshop, you’ll be able to:
> Understand how text embeddings have rapidly evolved in NLP tasks such as Word2Vec, recurrent neural network (RNN)-based embeddings, and Transformers
> See how Transformer architecture features, especially self-attention, are used to create language models without RNNs
> Use self-supervision to improve the Transformer architecture in BERT, Megatron, and other variants for superior NLP results
> Leverage pre-trained, modern NLP models to solve multiple tasks such as text classification, NER, and question answering
> Manage inference challenges and deploy refined models for live applications
Why Choose NVIDIA Deep Learning Institute for Hands-On Training?
Data Scientist, NVIDIA
Liang is a data scientist with years of experiences in various industry for NLP and big data analytics projects. She holds Ph.D. of computer science.
SINGAPORE HEALTHCARE AI DATATHON AND EXPO 2021