Byte-Sized Deep Learning Series: Understanding Language
- Created By raju2006
- Last Updated February 21st, 2025
- Overview
- Prerequisite
- Audience
- Curriculum
Session 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
Learning Objectives:
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)
- 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.
The curriculum is empty
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