Book Image

Machine Learning with Swift

By : Jojo Moolayil, Alexander Sosnovshchenko, Oleksandr Baiev
Book Image

Machine Learning with Swift

By: Jojo Moolayil, Alexander Sosnovshchenko, Oleksandr Baiev

Overview of this book

Machine learning as a field promises to bring increased intelligence to the software by helping us learn and analyse information efficiently and discover certain patterns that humans cannot. This book will be your guide as you embark on an exciting journey in machine learning using the popular Swift language. We’ll start with machine learning basics in the first part of the book to develop a lasting intuition about fundamental machine learning concepts. We explore various supervised and unsupervised statistical learning techniques and how to implement them in Swift, while the third section walks you through deep learning techniques with the help of typical real-world cases. In the last section, we will dive into some hard core topics such as model compression, GPU acceleration and provide some recommendations to avoid common mistakes during machine learning application development. By the end of the book, you'll be able to develop intelligent applications written in Swift that can learn for themselves.
Table of Contents (18 chapters)
Title Page
Packt Upsell

iOS application

To use vectors in an iOS application, we must export them in a binary format:

In [47]: 
model.wv.save_word2vec_format(fname='MarkTwain.bin', binary=True) 

This binary contains words and their embedding vectors, all of the same length. The original implementation of Word2Vec was written in C, so I took it and adapted the code for our purpose—to parse the binary file and find closest words to the one that we specify.

Chatbot anatomy

Most chatbots look like reincarnations of console applications: you have a predefined set of commands and the bot produces an output for every command of yours. Someone even joked that Linux includes an awesome chatbot called console. But they don't always have to be that way. Let's see how we can make them more interesting. A typical chatbot consists of one or several input streams, a brain, and output streams. Inputs can be a keyboard, voice recognition, or set of predefined phrases. The brain is a sort of algorithm for transforming input into output...