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Machine Learning with Swift

Machine Learning with Swift

By : Alexander Sosnovshchenko , Jojo Moolayil, Oleksandr Baiev
3 (1)
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Machine Learning with Swift

Machine Learning with Swift

3 (1)
By: Alexander Sosnovshchenko , Jojo Moolayil, 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 (14 chapters)
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Loading the data

As usual, first we add some magic to display images inline in the Jupyter:

%matplotlib inline 

We're using Pandas to handle our data:

import pandas 

Please, visit the Kaggle site and download the dataset: https://www.kaggle.com/c/challenges-in-representation-learning-facial-expression-recognition-challenge

Load the dataset into the memory:

data = pandas.read_csv("fer2013/fer2013.csv") 

Dataset consists of gray scale face photos encoded as pixel intensities. 48 x 48 gives 2304 pixels for each. Every image is marked according to the emotion on the face.

data.head() 
emotion  pixels   Usage 
0  0  70 80 82 72 58 58 60 63 54 58 60 48 89 115 121...  Training 
1  0  151 150 147 155 148 133 111 140 170 174 182 15...  Training 
2  2  231 212 156 164 174 138 161 173 182 200 106 38...  Training 
3  4  24 32 36 30 32 23 19 20 30 41 21 22 32 34 21 1.....

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