Byte-Sized Deep Learning Series: Applied Deep Learning for Natural Language Understanding
- Created By raju2006
- Last Updated December 5th, 2023
- Overview
- Prerequisite
- Audience
- Audience
- Curriculum
Description:
This 90-minute session will explore the application of deep learning models known as transformers to solve common natural language understanding tasks (e.g., question answering, sentiment classification, text summarization, text generation). Learners will use the popular Hugging Face library.
Course Code/Duration:
BDT151 / 90 minutes
- Learners should have a basic knowledge of Python programming.
- This course is for those who would like to understand how to apply deep learning to common natural language understanding tasks.
- This course is for those who would like to understand how to apply deep learning to common natural language understanding tasks.
Course Outline:
During this course, you will have the opportunity to:
- Understand the transformer model and why it is superior to previous approaches to natural language understanding.
- Learn how to use the popular Hugging Face library to solve common use cases.
- Apply pre-trained models to answer questions related to a corpus of text, summarize text, generate novel text, and several other use cases including paraphrasing, sentiment classification, and text completion.
Training material provided: Yes (Digital format)
The curriculum is empty
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