Natural Language Processing with PyTorchlow

If you’re a developer or data scientist new to NLP and deep learning, this practical guide shows you how to apply these methods using PyTorch, a Python-based deep learning library.

Format: Paperback / softback
Length: 256 pages
Publication date: 05 February 2019
Publisher: O'Reilly Media, Inc, USA

Natural Language Processing (NLP) is a field that offers endless possibilities for solving problems in artificial intelligence, enabling the development of innovative products like Amazon Alexa and Google Translate. If you're a developer or data scientist who's new to NLP and deep learning, this comprehensive guide will help you leverage these powerful methods using PyTorch, a Python-based deep learning library.

Authors Delip Rao and Brian McMahon, both experts in NLP and deep learning, provide a solid foundation for understanding NLP and deep learning algorithms. They guide you through the process of using PyTorch to build applications that address specific text-related problems you encounter. Each chapter includes numerous code examples and illustrations to reinforce the concepts discussed.

In this guide, you'll delve into computational graphs and the supervised learning paradigm. You'll learn the basics of the PyTorch optimized tensor manipulation library, which is essential for efficient data processing in deep learning models. You'll also gain an overview of traditional NLP concepts and methods, such as tokenization, stemming, and part-of-speech tagging.

Next, you'll explore the fundamental ideas behind building neural networks, including convolutional neural networks (CNNs) and recurrent neural networks (RNNs). You'll learn how to use embeddings to represent words, sentences, documents, and other features, which are crucial for capturing the contextual information in text.

Sequence prediction and generation are important tasks in NLP, and you'll learn how to use PyTorch to build sequence-to-sequence models. You'll explore design patterns for building production NLP systems, which are designed to handle large-scale text datasets and deliver accurate results.

By the end of this guide, you'll have a comprehensive understanding of NLP and deep learning using PyTorch. You'll be equipped to apply these methods to real-world problems and build innovative solutions that leverage the power of natural language processing. Whether you're a seasoned developer or just starting your journey in NLP, this guide will be your invaluable resource.

Weight: 444g
Dimension: 179 x 233 x 13 (mm)
ISBN-13: 9781491978238