Develop Intelligent iOS Apps with Swift Understand Texts, Classify Sentiments, and Autodetect Answers in Text Using NLP

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, extracting text with OCR, generating sentences with AI, categorizing the sentiment of text, 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 broughtaccessible 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.

 

What You'll Learn

Incorporate Apple tools such as CreateML and CoreML into your Swift toolbox
• Convert state-of-the-art NLP models to CoreML from Keras
• Teach your apps to predict words while users are typing with smart auto-complete 

 

Who This Book Is For

 

Novice developers and programmers who wish to implement natural language processing in their iOS applications and those who want to learn Apple's native ML tools.

 

Chapter 1: Gentle Introduction to ML and NLP.- Chapter 2: Introduction to Apple ML Tools.- Chapter 3: Text Classification.- Chapter 4: Text Generation.- Chapter 5: Find Answers in a Text Document.- Chapter 6: Text Summarization.- Chapter 7: Integrating Keras Models. 

Özgür Sahin has been developing iOS software since 2012. He holds a bachelors degree in computer engineering and a masters in deep learning. Currently, he serves as CTO for Iceberg Tech, an AI solutions startup. He develops iOS apps focused on AR and Core ML using face recognition and demographic detection capabilities. He writes iOS machine learning tutorials for Fritz AI and also runs a local iOS machine learning mail group to teach iOS ML tools to Turkey. In his free time, Özgür develops deep learning based iOS apps.