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Sahin

Develop Intelligent iOS Apps with Swift

Understand Texts, Classify Sentiments, and Autodetect Answers in Text Using NLP

Jetzt vorbestellen! Wir liefern bei Erscheinen (Erscheint vsl. November 2020)

Buch. Softcover

1st ed.. 2020

xx, 130 S. Bibliographien

In englischer Sprache

Apress. ISBN 978-1-4842-6420-1

Format (B x L): 15,5 x 23,5 cm

Produktbeschreibung

Build smart apps capable of analyzing language and performing language-specific tasks, such as script identification, tokenization, lemmatization, part-of-speech tagging, and named entity recognition. This book will get you started in the world of building literate, language understanding apps. Cutting edge ML tools from Apple like CreateML, CoreML, and TuriCreate will become natural parts of your development toolbox as you construct intelligent, text-based apps. You'll explore a wide range of text processing topics, including reprocessing text, training custom machine learning models, converting state-of-the-art NLP models to CoreML from Keras, evaluating models, and deploying models to your iOS apps. You’ll develop sample apps to learn by doing. These include apps with functions for detecting spam SMS, developing smart auto-complete that predicts words while typing, categorizing the sentiment of text, identifying an author from his/her writings, developing intelligent apps that read text and answers questions, converting speech to text, detecting parts of speech, and identifying people, places, and organizations in text. Smart app development involves mainly teaching apps to learn and understand input without explicit prompts from their users. These apps understand what is in images, predict future behavior, and analyze texts. Thanks to natural language processing, iOS can auto-fix typos and Siri can understand what you're saying. With Apple’s own easy-to-use tool, Create ML, they’ve brought accesible ML capabilities to developers. Develop Intelligent iOS Apps with Swift will show you how to easily create text classification and numerous other kinds of models. You will: - Incorporate Apple tools such as CreateML and CoreML into your Swift toolbox - Convert state-of-the-art NLP models to CoreML from Keras and TensorFlow - Teach your apps to predict words while users are typing with smart auto-complete

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