Da: Ria Christie Collections, Uxbridge, Regno Unito
EUR 34,60
Quantità: Più di 20 disponibili
Aggiungi al carrelloCondizione: New. In.
Da: Ria Christie Collections, Uxbridge, Regno Unito
EUR 49,99
Quantità: Più di 20 disponibili
Aggiungi al carrelloCondizione: New. In.
EUR 38,09
Quantità: 1 disponibili
Aggiungi al carrelloPaperback. Condizione: new. Paperback. Deep Learning for Natural Language Processing is a comprehensive guide that explores the intersection of deep learning techniques and natural language processing (NLP). The book begins with an overview of fundamental NLP concepts and progresses into advanced deep learning architectures, including feedforward neural networks, recurrent neural networks (RNNs), long short-term memory (LSTM) networks, and attention mechanisms. Each chapter offers clear explanations of the theory behind the models, followed by practical code examples using popular deep learning frameworks like TensorFlow and PyTorch.Readers will learn how to preprocess text data, build word embeddings, and work with sequence models to handle real-world language data. The authors also cover cutting-edge techniques such as transformers, BERT, and GPT, which have revolutionized NLP tasks. Emphasizing both theory and hands-on practice, this book is ideal for students, researchers, and professionals looking to deepen their understanding of deep learning methods in the context of language.By the end of the book, readers will be equipped with the skills to tackle a wide range of NLP problems using deep learning, and will gain a deeper appreciation for the powerful combination of deep learning and natural language processing in transforming industries like healthcare, finance, and customer service. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.
EUR 55,68
Quantità: 1 disponibili
Aggiungi al carrelloHardcover. Condizione: new. Hardcover. Deep Learning for Natural Language Processing is a comprehensive guide that explores the intersection of deep learning techniques and natural language processing (NLP). The book begins with an overview of fundamental NLP concepts and progresses into advanced deep learning architectures, including feedforward neural networks, recurrent neural networks (RNNs), long short-term memory (LSTM) networks, and attention mechanisms. Each chapter offers clear explanations of the theory behind the models, followed by practical code examples using popular deep learning frameworks like TensorFlow and PyTorch.Readers will learn how to preprocess text data, build word embeddings, and work with sequence models to handle real-world language data. The authors also cover cutting-edge techniques such as transformers, BERT, and GPT, which have revolutionized NLP tasks. Emphasizing both theory and hands-on practice, this book is ideal for students, researchers, and professionals looking to deepen their understanding of deep learning methods in the context of language.By the end of the book, readers will be equipped with the skills to tackle a wide range of NLP problems using deep learning, and will gain a deeper appreciation for the powerful combination of deep learning and natural language processing in transforming industries like healthcare, finance, and customer service. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.
Da: AHA-BUCH GmbH, Einbeck, Germania
EUR 46,00
Quantità: 2 disponibili
Aggiungi al carrelloTaschenbuch. Condizione: Neu. Neuware - Deep Learning for Natural Language Processing is a comprehensive guide that explores the intersection of deep learning techniques and natural language processing (NLP).
Da: AHA-BUCH GmbH, Einbeck, Germania
EUR 76,00
Quantità: 2 disponibili
Aggiungi al carrelloBuch. Condizione: Neu. Neuware - Deep Learning for Natural Language Processing is a comprehensive guide that explores the intersection of deep learning techniques and natural language processing (NLP).
Da: Grand Eagle Retail, Bensenville, IL, U.S.A.
Paperback. Condizione: new. Paperback. Deep Learning for Natural Language Processing is a comprehensive guide that explores the intersection of deep learning techniques and natural language processing (NLP). The book begins with an overview of fundamental NLP concepts and progresses into advanced deep learning architectures, including feedforward neural networks, recurrent neural networks (RNNs), long short-term memory (LSTM) networks, and attention mechanisms. Each chapter offers clear explanations of the theory behind the models, followed by practical code examples using popular deep learning frameworks like TensorFlow and PyTorch.Readers will learn how to preprocess text data, build word embeddings, and work with sequence models to handle real-world language data. The authors also cover cutting-edge techniques such as transformers, BERT, and GPT, which have revolutionized NLP tasks. Emphasizing both theory and hands-on practice, this book is ideal for students, researchers, and professionals looking to deepen their understanding of deep learning methods in the context of language.By the end of the book, readers will be equipped with the skills to tackle a wide range of NLP problems using deep learning, and will gain a deeper appreciation for the powerful combination of deep learning and natural language processing in transforming industries like healthcare, finance, and customer service. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
Da: PBShop.store US, Wood Dale, IL, U.S.A.
PAP. Condizione: New. New Book. Shipped from UK. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.
Da: PBShop.store UK, Fairford, GLOS, Regno Unito
EUR 35,43
Quantità: Più di 20 disponibili
Aggiungi al carrelloPAP. Condizione: New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.
Da: Grand Eagle Retail, Bensenville, IL, U.S.A.
Hardcover. Condizione: new. Hardcover. Deep Learning for Natural Language Processing is a comprehensive guide that explores the intersection of deep learning techniques and natural language processing (NLP). The book begins with an overview of fundamental NLP concepts and progresses into advanced deep learning architectures, including feedforward neural networks, recurrent neural networks (RNNs), long short-term memory (LSTM) networks, and attention mechanisms. Each chapter offers clear explanations of the theory behind the models, followed by practical code examples using popular deep learning frameworks like TensorFlow and PyTorch.Readers will learn how to preprocess text data, build word embeddings, and work with sequence models to handle real-world language data. The authors also cover cutting-edge techniques such as transformers, BERT, and GPT, which have revolutionized NLP tasks. Emphasizing both theory and hands-on practice, this book is ideal for students, researchers, and professionals looking to deepen their understanding of deep learning methods in the context of language.By the end of the book, readers will be equipped with the skills to tackle a wide range of NLP problems using deep learning, and will gain a deeper appreciation for the powerful combination of deep learning and natural language processing in transforming industries like healthcare, finance, and customer service. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
Da: PBShop.store US, Wood Dale, IL, U.S.A.
HRD. Condizione: New. New Book. Shipped from UK. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.
Da: PBShop.store UK, Fairford, GLOS, Regno Unito
EUR 51,46
Quantità: Più di 20 disponibili
Aggiungi al carrelloHRD. Condizione: New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.