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Natural Language Processing with GPT

Natural Language Processing with GPT

Author(s): Ernesto Lee

Edition: 1

Copyright: 2024

Edition: 1

Copyright: 2024

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Print Package

$72.00

ISBN 9798765799604

Details Print Prod w/KHPContent Code 180 days

Faculty Review Copy

Ebook Package

$36.00

ISBN 9798765799611

Details eBook w/KHPContent Access 180 days

Faculty Review Copy

Natural Language Processing with GPT by Dr. Ernesto Lee is a comprehensive guide designed to explore the intricate details of NLP techniques, with a focus on practical applications using GPT (Generative Pretrained Transformers). The book provides readers with a strong foundation in the field of NLP, starting from basic text analytics concepts and moving into advanced machine learning and deep learning approaches. 

Key chapters in the book include:

  • Introduction to NLP: An overview of the field, outlining essential NLP concepts. 
  • Word Vectorization: Methods of transforming words into vectors for machine learning models.
  • Text Classification: A two-part deep dive into using machine learning for categorizing text data.
  • Word Embeddings: Discusses popular embedding techniques like Word2Vec to represent words in high-dimensional space.
  • Deep Learning and LSTM: Covers the implementation of deep learning architectures, focusing on sequential models like Long Short-Term Memory (LSTM).
  • Attention and Transformers: Introduces the pivotal role of transformers in NLP and deep learning, setting the stage for modern models like GPT and BERT.
  • BERT: Explores another transformer-based model that excels in a wide range of NLP tasks. 

The final chapters empower readers to build, fine-tune, and manage their own GPT models, providing both theoretical and practical insights. The book is ideal for students, developers, and professionals interested in advancing their understanding of NLP and applying GPT-based solutions to real-world problems.

Chapter 1 Introduction to NLP 
Chapter 2 Word Vectorization 
Chapter 3 Text Classification with Machine Learning: I 
Chapter 4 Text Classification with Machine Learning: II 
Chapter 5 Word Embedding (Word2Vec) 
Chapter 6 Deep Learning 
Chapter 7 Deep Learning: Part II 
Chapter 8 Long Short Term Memory (LSTM) 
Chapter 9 Sequence-to-sequence Modeling 
Chapter 10 Attention and Transformers 
Chapter 11 BERT

Ernesto Lee

Dr. Ernesto Lee is a Data Analytics and AI faculty member at Miami Dade College who also happens to be an expert in Artificial Intelligence and Education, with a significant focus on artificial general intelligence through cutting-edge technologies. His influential research has garnered over 1,200 citations in just 18 months. Dr. Lee's notable publications include "Integrating Learning Analytics and Collaborative Learning for Improving Student’s Academic Performance" and "Blood cancer prediction using leukemia microarray gene data and hybrid logistic vector trees model." Both of these articles were published by IEEE and Scientific Reports, top academic journals. 

As the founder of Blockchain Training Alliance, an Applied AI and Blockchain company, Dr. Lee led the training of over 300,000 students in two years before the company was acquired by a publicly traded firm. His achievements reflect his dedication to advancing educational technology. Dr. Lee is also the author of an upcoming textbook: "Natural Language Processing with GPT" published by Kendall Hunt.

Natural Language Processing with GPT by Dr. Ernesto Lee is a comprehensive guide designed to explore the intricate details of NLP techniques, with a focus on practical applications using GPT (Generative Pretrained Transformers). The book provides readers with a strong foundation in the field of NLP, starting from basic text analytics concepts and moving into advanced machine learning and deep learning approaches. 

Key chapters in the book include:

  • Introduction to NLP: An overview of the field, outlining essential NLP concepts. 
  • Word Vectorization: Methods of transforming words into vectors for machine learning models.
  • Text Classification: A two-part deep dive into using machine learning for categorizing text data.
  • Word Embeddings: Discusses popular embedding techniques like Word2Vec to represent words in high-dimensional space.
  • Deep Learning and LSTM: Covers the implementation of deep learning architectures, focusing on sequential models like Long Short-Term Memory (LSTM).
  • Attention and Transformers: Introduces the pivotal role of transformers in NLP and deep learning, setting the stage for modern models like GPT and BERT.
  • BERT: Explores another transformer-based model that excels in a wide range of NLP tasks. 

The final chapters empower readers to build, fine-tune, and manage their own GPT models, providing both theoretical and practical insights. The book is ideal for students, developers, and professionals interested in advancing their understanding of NLP and applying GPT-based solutions to real-world problems.

Chapter 1 Introduction to NLP 
Chapter 2 Word Vectorization 
Chapter 3 Text Classification with Machine Learning: I 
Chapter 4 Text Classification with Machine Learning: II 
Chapter 5 Word Embedding (Word2Vec) 
Chapter 6 Deep Learning 
Chapter 7 Deep Learning: Part II 
Chapter 8 Long Short Term Memory (LSTM) 
Chapter 9 Sequence-to-sequence Modeling 
Chapter 10 Attention and Transformers 
Chapter 11 BERT

Ernesto Lee
Ernesto Lee

Dr. Ernesto Lee is a Data Analytics and AI faculty member at Miami Dade College who also happens to be an expert in Artificial Intelligence and Education, with a significant focus on artificial general intelligence through cutting-edge technologies. His influential research has garnered over 1,200 citations in just 18 months. Dr. Lee's notable publications include "Integrating Learning Analytics and Collaborative Learning for Improving Student’s Academic Performance" and "Blood cancer prediction using leukemia microarray gene data and hybrid logistic vector trees model." Both of these articles were published by IEEE and Scientific Reports, top academic journals. 

As the founder of Blockchain Training Alliance, an Applied AI and Blockchain company, Dr. Lee led the training of over 300,000 students in two years before the company was acquired by a publicly traded firm. His achievements reflect his dedication to advancing educational technology. Dr. Lee is also the author of an upcoming textbook: "Natural Language Processing with GPT" published by Kendall Hunt.