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LinkedIn Learning

Applied AI: Building NLP Apps with Hugging Face Transformers

via LinkedIn Learning

Overview

Learn how to build natural language processing (NLP) applications with pretrained transformers in Hugging Face, the popular machine learning platform.

Syllabus

Introduction
  • Building NLP apps with Transformers
  • Course coverage and prerequisites
  • Setting up the exercise files
1. Question-Answering (Qu-An)
  • Question-answering in NLP
  • Types of question-answering
  • Building a Qu-An pipeline
  • The SQuAD metric
  • Evaluating Qu-An performance
2. Text Summarization
  • Text summarization in NLP
  • The BART model architecture
  • Summarization with pipelines
  • The ROUGE score
  • Evaluating with ROUGE
3. Natural Language Generation
  • Natural language generation in NLP
  • Content creation with Transformers
  • Conversation generation
  • Chatbot conversation example
  • Machine translation in NLP
  • Translating with Hugging Face Transformers
4. Customizing Models with Transfer Learning
  • Training a custom model
  • Loading a Hugging Face dataset
  • Encoding and preprocessing the dataset
  • Customizing the model architecture
  • Training the sentiment model
  • Predicting with the custom model
5. Deploying and Using Hugging Face Models
  • Inference challenges with Transformers
  • Customizing pretrained models
  • Model compression overview
  • Serving multiple models
Conclusion
  • Continuing with Hugging Face

Taught by

Kumaran Ponnambalam

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4.7 rating at LinkedIn Learning based on 114 ratings

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