Build advanced Natural Language Understanding Systems by acquiring data and selecting appropriate technology. Key Featur
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English Pages 326 Year 2023
Table of contents :
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