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Natural Language Understanding, Related Technologies, and Natural Language Applications
Identifying Practical Natural Language Understanding Problems Approaches to Natural Language Understanding - Rule-Based Systems, Machine Learning, and Deep Learning Selecting Libraries and Tools for Natural Language Understanding Natural Language Data - Finding and Preparing Data Exploring and Visualizing Data Selecting Approaches and Representing Data Rule-Based Techniques Machine Learning Part 1 - Statistical Machine Learning Machine Learning Part 2 - Neural Networks and Deep Learning Techniques Machine Learning Part 3 - Transformers and Large Language Models Applying Unsupervised Learning Approaches How Well Does It Work? - Evaluation What to Do If the System Isn't Working Summary and Looking to the Future |