Transformers using python natural di rao (5 risultati)
- Brossura
Da: PBShop.store US, Wood Dale, IL, U.S.A.PBShop.store US
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 40,28
Spedizione gratuitaSpedito in U.S.A.Quantità: Più di 20 disponibili
PAP. Condizione: New. New Book. Shipped from UK. Established seller since 2000.
- Brossura
Da: PBShop.store UK, Fairford, GLOS, Regno UnitoPBShop.store UK
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 34,25
EUR 7,91 spedizioneSpedito da Regno Unito a U.S.A.Quantità: Più di 20 disponibili
PAP. Condizione: New. New Book. Shipped from UK. Established seller since 2000.
Transformers Using Python for Natural Language Processing: Fundamentals, Principles and Applications
- Brossura
- Print on Demand
Da: California Books, Miami, FL, U.S.A.California Books
Contatta il venditoreVenditore con 4 stelleCondizione: Nuovo
EUR 33,90
Spedizione gratuitaSpedito in U.S.A.Quantità: Più di 20 disponibili
Condizione: New. Print on Demand.
- Brossura
- Print on Demand
Da: Grand Eagle Retail, Bensenville, IL, U.S.A.Grand Eagle Retail
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 39,25
Spedizione gratuitaSpedito in U.S.A.Quantità: 1 disponibili
Paperback. Condizione: new. Paperback. Natural language is one of the richest and most complex forms of data we create, and teaching machines to understand it has long been a central challenge in artificial intelligence. In recent years, transformer architectures have reshaped the landscape of Natural Language Processing (NLP),…enabling breakthroughs in language understanding, generation, translation, and reasoning at an unprecedented scale. Transformers Using Python for Natural Language Processing: Fundamentals, Principles and Applications introduces readers to this transformative shift, grounding advanced concepts in clear explanations and practical intuition. The book begins with the essential ideas behind NLP and deep learning, then carefully builds toward the core mechanics of transformers, attention mechanisms, embeddings, and model architectures without assuming extensive prior expertise. Designed with both learning and application in mind, this book emphasizes hands-on experimentation using Python and widely adopted NLP libraries. Readers will explore how theoretical principles translate into working systems for real-world tasks such as text classification, sentiment analysis, summarization, and language generation. By blending mathematical insight, conceptual clarity, and practical code examples, this book aims to bridge the gap between foundational theory and modern NLP practice, empowering students, researchers, and practitioners to confidently design, fine-tune, and deploy transformer-based models in diverse applications. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
- Brossura
- Print on Demand
Da: CitiRetail, Stevenage, Regno UnitoCitiRetail
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 38,56
EUR 43,30 spedizioneSpedito da Regno Unito a U.S.A.Quantità: 1 disponibili
Paperback. Condizione: new. Paperback. Natural language is one of the richest and most complex forms of data we create, and teaching machines to understand it has long been a central challenge in artificial intelligence. In recent years, transformer architectures have reshaped the landscape of Natural Language Processing (NLP),…enabling breakthroughs in language understanding, generation, translation, and reasoning at an unprecedented scale. Transformers Using Python for Natural Language Processing: Fundamentals, Principles and Applications introduces readers to this transformative shift, grounding advanced concepts in clear explanations and practical intuition. The book begins with the essential ideas behind NLP and deep learning, then carefully builds toward the core mechanics of transformers, attention mechanisms, embeddings, and model architectures without assuming extensive prior expertise. Designed with both learning and application in mind, this book emphasizes hands-on experimentation using Python and widely adopted NLP libraries. Readers will explore how theoretical principles translate into working systems for real-world tasks such as text classification, sentiment analysis, summarization, and language generation. By blending mathematical insight, conceptual clarity, and practical code examples, this book aims to bridge the gap between foundational theory and modern NLP practice, empowering students, researchers, and practitioners to confidently design, fine-tune, and deploy transformer-based models in diverse applications. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.
