Introduction
Getting started with Transformers
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Course coverage and prerequisites
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Setting up the exercise files
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1. Machine Learning for NLP
Natural language processing
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ML process for NLP
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Labeling for NLP
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Tokenization
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Vectorization
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2. Introduction to Transformers
What is a Transformer?
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Positional encoding
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Attention in Transformers
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The encoder
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The decoder
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Transformer training and inference
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3. Pretrained Transformers
Challenges with building Transformers
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A language model
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Pretrained Transformer models
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The BERT Transformer
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The GPT Transformer
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The T5 Transformer
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4. Introduction to Hugging Face
Introduction to Hugging Face
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Pretrained models in Hugging Face
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Datasets in Hugging Face
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Pipelines in Hugging Face
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Training with Hugging Face
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5. Sentiment Analysis with Hugging Face
The sentiment analysis problem
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Reviewing pipeline tasks
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Loading a pipeline
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Predicting sentiment with Pipelines
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Using a custom model
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6. Named Entity Recognition
Introduction to named entity recognition
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Running the standard NER pipeline
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Understanding the model architecture
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Reviewing model configuration
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Using a custom model and tokenizer
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Conclusion
Continuing with Transformers
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Ex_Files_Applied_AI_Getting_Started.zip
(11 KB)