Natural language understanding with Python combine natural language technology, deep learning, and large language models to create human-like comprehension
Unleash the full potential of natural language understanding (NLU) and create impeccable systems by mastering the art of data acquisition and technology selection Purchase of the print or Kindle book includes a free PDF eBook Key Features Master NLU concepts from basic text processing to advanced de...
| Otros Autores: | |
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| Formato: | Libro electrónico |
| Idioma: | Inglés |
| Publicado: |
Birmingham, England :
Packt Publishing Ltd
[2023]
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| Edición: | 1st ed |
| Materias: | |
| Ver en Biblioteca Universitat Ramon Llull: | https://discovery.url.edu/permalink/34CSUC_URL/1im36ta/alma991009755147406719 |
Tabla de Contenidos:
- 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.
