| Description |
1 online resource (514 pages) : illustrations |
| Series |
Expert insight |
|
Expert insight.
|
| Note |
Includes index. |
| 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 |
| 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. |
| Subject |
TensorFlow.
|
|
Natural language processing (Computer science)
|
|
Machine learning.
|
|
Traitement automatique des langues naturelles. |
|
Apprentissage automatique. |
|
Machine learning |
|
Natural language processing (Computer science) |
| Added Author |
Lopatenko, Andrei, writer of foreword..
|
| Other Form: |
Print version : 9781838641351 |
| ISBN |
9781838647742 (ebook) |
|
1838647740 |
|
More Resources