Develop Intelligent IOS Apps with Swift: Understand Texts, Classify Sentiments, and Autodetect Answers in Text Using Nlp


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Description

Chapter 1: Gentle Introduction to ML and NLP

Chapter Goal: Present general ideas of ML and how NLP works

- Intro to ML

- Intro to NLP

Chapter 2: Apple's ML Tools

Chapter Goal: Learn the tools that Apple provides for ML

- CoreML

- CreateML

- TuriCreate

Chapter 3: Text Classification

Chapter Goal: Learn the tools that Apple provides for ML

- Spam SMS classification

- Find the author of a writing

- TuriCreate

Chapter 4: Natural Language Framework

Chapter Goal: Learn iOS's built in NLP capabilities

- Tokenization

- Classify nouns, verbs, and adjectives

- Detect people, places, and organizations in text

Chapter 5: Find Answers to Questions in a Text Document

Chapter Goal: Use BERT model to find the answer to a user's question in a body of text.

- BERT model

- Text handling

Chapter 6: Advanced Usages

- Convert NLP models from Keras to Core ML

- Convert NLP models from TensorFlow to Core ML



Author: Özgür Sahin
Publisher: Apress
Published: 12/27/2020
Pages: 169
Binding Type: Paperback
Weight: 0.59lbs
Size: 9.21h x 6.14w x 0.39d
ISBN13: 9781484264201
ISBN10: 1484264207
BISAC Categories:
- Computers | Programming | Macintosh

About the Author

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.