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
Contributors
Preface
Index

Environment setup


To train the deep CNN, you will need a computer with a CUDA-compatible GPU. I used an Ubuntu 16.x machine with NVidia GTX980 GPU for model training, and a macOS machine to convert the model to Core ML format. If you don't have CUDA-compatible GPU, you can try to train the model on CPU; but be aware that this will take a lot of time. Also, the trained model for this chapter is available in the supplementary materials, so if you prefer not to contribute to the global warming by retraining the model from scratch, it's also possible.

Here's a list of what should be installed on your system to train the network:

  • Latest NVIDIA drivers
  • CUDA 8.0
  • cuDNN 5.1
  • Python 2.7
  • tensorflow-gpu (or TensorFlow for CPU-only mode)
  • Keras
  • Keras-viz
  • Matplotlib, Pandas

Please, refer to the official sites for the installation instructions.