Natural language processing with TensorFlow : the definitive NLP book to implement the most sought-after machine learning models and tasks / Thushan Ganegedara and Andrei Lopatenko.

Format:

Book

Author/Creator:

Ganegedara, Thushan, author.

Lopatenko, Andrei, author.

Series:

Expert insight.

Expert insight

Language:

English

Subjects (All):

TensorFlow.

Natural language processing (Computer science).

Machine learning.

Physical Description:

1 online resource (515 pages)

Edition:

Second edition.

Place of Publication:

Birmingham, England : Packt Publishing, [2022]

Biography/History:

Ganegedara Thushan: Thushan is a seasoned ML practitioner with 4+ years of experience in the industry. Currently he is a senior machine learning engineer at Canva; an Australian startup that founded the online visual design software, Canva, serving millions of customers. His efforts are particularly concentrated in the search and recommendations group working on both visual and textual content. Prior to Canva, Thushan was a senior data scientist at QBE Insurance; an Australian Insurance company. Thushan was developing ML solutions for use-cases related to insurance claims. He also led efforts in developing a Speech2Text pipeline there. He obtained his PhD specializing in machine learning from the University of Sydney in 2018.

Summary:

Learning how to solve natural language processing (NLP) problems is an important skill to master due to the explosive growth of data combined with the demand for machine learning solutions in production. Natural Language Processing with TensorFlow, Second Edition, will teach you how to solve common real-world NLP problems with a variety of deep learning model architectures. The book starts by getting readers familiar with NLP and the basics of TensorFlow. Then, it gradually teaches you different facets of TensorFlow 2.x. In the following chapters, you then learn how to generate powerful word vectors, classify text, generate new text, and generate image captions, among other exciting use-cases of real-world NLP. TensorFlow has evolved to be an ecosystem that supports a machine learning workflow through ingesting and transforming data, building models, monitoring, and productionization. We will then read text directly from files and perform the required transformations through a TensorFlow data pipeline. We will also see how to use a versatile visualization tool known as TensorBoard to visualize our models. By the end of this NLP book, you will be comfortable with using TensorFlow to build deep learning models with many different architectures, and efficiently ingest data using TensorFlow Additionally, you'll be able to confidently use TensorFlow throughout your machine learning workflow.

Contents:

Chapter 1: Introduction to natural language processing

Chapter 2: Understanding TensorFlow 2

Chapter 3: Word2vec: learning word embeddings

Chapter 4: Advanced word vector algorithms

Chapter 5: Sentence classification with convolutional neural networks

Chapter 6: Recurrent neural networks

Chapter 7: Understanding long short-term memory networks

Chapter 8: Applications of LSTM: generating text

Chapter 9: Sequence-to-sequence learning: neural machine translation

Chapter 10: Transformers

Chapter 11: Image captioning with transformers

Appendix A: Mathematical foundations and advanced TensorFlow

Notes:

Includes index.

Includes bibliographical references and index.

Description based on print version record.

ISBN:

9781838647742

1838647740

OCLC:

1338150602