Applied AI: Building NLP Apps with Hugging Face Transformers
57mIntermediate2023-02-02
Authors
Kumaran Ponnambalam
Working with data for 20+ years
Course details
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.
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.
Skills covered
JupyterHugging FaceNatural Language Processing (NLP)Machine LearningAdvancedPythonArtificial Intelligence (AI)Open Source
Concepts
Introduction
- Building NLP apps with Transformers
- Course coverage and prerequisites
- Setting up the exercise files
Question-Answering (Qu-An)
- Question-answering in NLP
- Types of question-answering
- Building a Qu-An pipeline
- The SQuAD metric
- Evaluating Qu-An performance
Text Summarization
- Text summarization in NLP
- The BART model architecture
- Summarization with pipelines
- The ROUGE score
- Evaluating with ROUGE
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
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
Deploying and Using Hugging Face Models
- Inference challenges with Transformers
- Customizing pretrained models
- Model compression overview
- Serving multiple models
Conclusion
- Continuing with Hugging Face