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Applied AI: Building NLP Apps with Hugging Face Transformers

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Looking to expand your skill set in deep learning? Find out how to use Hugging Face transformers to build natural language processing (NLP) applications. In this course, instructor Kumaran Ponnambalam shows you how to build models quickly and easily using pretrained transformers from the Hugging Face library.

Explore models designed for common NLP use cases such as question-answering, text summarization, text generation, translation, and more. Kumaran gives you tips for customizing models with transfer learning to meet the needs of specific use cases—improving your performance and lowering your costs along the way. Develop your know-how to identify and overcome common modeling challenges to ensure successful, error-free deployments. By the end of this course, you’ll be ready to adhere to the best practices and industry standards when you start applying your new skills on the job.


01 - Introduction
  • 01 - Building NLP apps with Transformers
  • 02 - Course coverage and prerequisites
  • 03 - Setting up the exercise files

  • 02 - 1. Question-Answering (Qu-An)
  • 04 - Question-answering in NLP
  • 05 - Types of question-answering
  • 06 - Building a Qu-An pipeline
  • 07 - The SQuAD metric
  • 08 - Evaluating Qu-An performance

  • 03 - 2. Text Summarization
  • 09 - Text summarization in NLP
  • 10 - The BART model architecture
  • 11 - Summarization with pipelines
  • 12 - The ROUGE score
  • 13 - Evaluating with ROUGE

  • 04 - 3. Natural Language Generation
  • 14 - Natural language generation in NLP
  • 15 - Content creation with Transformers
  • 16 - Conversation generation
  • 17 - Chatbot conversation example
  • 18 - Machine translation in NLP
  • 19 - Translating with Hugging Face Transformers

  • 05 - 4. Customizing Models with Transfer Learning
  • 20 - Training a custom model
  • 21 - Loading a Hugging Face dataset
  • 22 - Encoding and preprocessing the dataset
  • 23 - Customizing the model architecture
  • 24 - Training the sentiment model
  • 25 - Predicting with the custom model

  • 06 - 5. Deploying and Using Hugging Face Models
  • 26 - Inference challenges with Transformers
  • 27 - Customizing pretrained models
  • 28 - Model compression overview
  • 29 - Serving multiple models

  • 07 - Conclusion
  • 30 - Continuing with Hugging Face
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