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
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.
