Real-World Natural Language Processing: Practical Applications with Deep Learning

Real-World Natural Language Processing: Practical Applications with Deep Learning - Masato Hagiwara

Real-World Natural Language Processing: Practical Applications with Deep Learning


Real-world Natural Language Processing shows you how to build the practical NLP applications that are transforming the way humans and computers work together.

In Real-world Natural Language Processing you will learn how to:

Design, develop, and deploy useful NLP applications
Create named entity taggers
Build machine translation systems
Construct language generation systems and chatbots
Use advanced NLP concepts such as attention and transfer learning

Real-world Natural Language Processing teaches you how to create practical NLP applications without getting bogged down in complex language theory and the mathematics of deep learning. In this engaging book, you'll explore the core tools and techniques required to build a huge range of powerful NLP apps, including chatbots, language detectors, and text classifiers.

Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications.

About the technology
Training computers to interpret and generate speech and text is a monumental challenge, and the payoff for reducing labor and improving human/computer interaction is huge! Th e field of Natural Language Processing (NLP) is advancing rapidly, with countless new tools and practices. This unique book offers an innovative collection of NLP techniques with applications in machine translation, voice assistants, text generation, and more.

About the book
Real-world Natural Language Processing shows you how to build the practical NLP applications that are transforming the way humans and computers work together. Guided by clear explanations of each core NLP topic, you'll create many interesting applications including a sentiment analyzer and a chatbot. Along the way, you'll use Python and open source libraries like AllenNLP and HuggingFace Transformers to speed up your development process.

What's inside

Design, develop, and deploy useful NLP applications
Create named entity taggers
Build machine translation systems
Construct language generation systems and chatbots

About the reader
For Python programmers. No prior machine learning knowledge assumed.

About the author
Masato Hagiwara received his computer science PhD from Nagoya University in 2009. He has interned at Google and Microsoft Research, and worked at Duolingo as a Senior Machine Learning Engineer. He now runs his own research and consulting company.

Table of Contents
PART 1 BASICS
1 Introduction to natural language processing
2 Your first NLP application
3 Word and document embeddings
4 Sentence classification
5 Sequential labeling and language modeling
PART 2 ADVANCED MODELS
6 Sequence-to-sequence models
7 Convolutional neural networks
8 Attention and Transformer
9 Transfer learning with pretrained language models
PART 3 PUTTING INTO PRODUCTION
10 Best practices in developing NLP applications
11 Deploying and serving NLP applications

Citeste mai mult

transport gratuit

326.33Lei

Sau 32633 de puncte

!

Fiecare comanda noua reprezinta o investitie pentru viitoarele tale comenzi. Orice comanda plasata de pe un cont de utilizator primeste in schimb un numar de puncte de fidelitate, In conformitate cu regulile de conversiune stabilite. Punctele acumulate sunt incarcate automat in contul tau si pot fi folosite ulterior, pentru plata urmatoarelor comenzi.

Livrare in 3-5 saptamani

Descrierea produsului


Real-world Natural Language Processing shows you how to build the practical NLP applications that are transforming the way humans and computers work together.

In Real-world Natural Language Processing you will learn how to:

Design, develop, and deploy useful NLP applications
Create named entity taggers
Build machine translation systems
Construct language generation systems and chatbots
Use advanced NLP concepts such as attention and transfer learning

Real-world Natural Language Processing teaches you how to create practical NLP applications without getting bogged down in complex language theory and the mathematics of deep learning. In this engaging book, you'll explore the core tools and techniques required to build a huge range of powerful NLP apps, including chatbots, language detectors, and text classifiers.

Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications.

About the technology
Training computers to interpret and generate speech and text is a monumental challenge, and the payoff for reducing labor and improving human/computer interaction is huge! Th e field of Natural Language Processing (NLP) is advancing rapidly, with countless new tools and practices. This unique book offers an innovative collection of NLP techniques with applications in machine translation, voice assistants, text generation, and more.

About the book
Real-world Natural Language Processing shows you how to build the practical NLP applications that are transforming the way humans and computers work together. Guided by clear explanations of each core NLP topic, you'll create many interesting applications including a sentiment analyzer and a chatbot. Along the way, you'll use Python and open source libraries like AllenNLP and HuggingFace Transformers to speed up your development process.

What's inside

Design, develop, and deploy useful NLP applications
Create named entity taggers
Build machine translation systems
Construct language generation systems and chatbots

About the reader
For Python programmers. No prior machine learning knowledge assumed.

About the author
Masato Hagiwara received his computer science PhD from Nagoya University in 2009. He has interned at Google and Microsoft Research, and worked at Duolingo as a Senior Machine Learning Engineer. He now runs his own research and consulting company.

Table of Contents
PART 1 BASICS
1 Introduction to natural language processing
2 Your first NLP application
3 Word and document embeddings
4 Sentence classification
5 Sequential labeling and language modeling
PART 2 ADVANCED MODELS
6 Sequence-to-sequence models
7 Convolutional neural networks
8 Attention and Transformer
9 Transfer learning with pretrained language models
PART 3 PUTTING INTO PRODUCTION
10 Best practices in developing NLP applications
11 Deploying and serving NLP applications

Citeste mai mult

Parerea ta e inspiratie pentru comunitatea Libris!

Noi suntem despre carti, si la fel este si

Newsletter-ul nostru.

Aboneaza-te la vestile literare si primesti un cupon de -10% pentru viitoarea ta comanda!

*Reducerea aplicata prin cupon nu se cumuleaza, ci se aplica reducerea cea mai mare.

Ma abonez image one
Ma abonez image one