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Machine Learning with Swift

You're reading from   Machine Learning with Swift Artificial Intelligence for iOS

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Product type Paperback
Published in Feb 2018
Publisher Packt
ISBN-13 9781787121515
Length 378 pages
Edition 1st Edition
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Authors (3):
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Jojo Moolayil Jojo Moolayil
Author Profile Icon Jojo Moolayil
Jojo Moolayil
Oleksandr Baiev Oleksandr Baiev
Author Profile Icon Oleksandr Baiev
Oleksandr Baiev
Alexander Sosnovshchenko Alexander Sosnovshchenko
Author Profile Icon Alexander Sosnovshchenko
Alexander Sosnovshchenko
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Table of Contents (14) Chapters Close

Preface 1. Getting Started with Machine Learning FREE CHAPTER 2. Classification – Decision Tree Learning 3. K-Nearest Neighbors Classifier 4. K-Means Clustering 5. Association Rule Learning 6. Linear Regression and Gradient Descent 7. Linear Classifier and Logistic Regression 8. Neural Networks 9. Convolutional Neural Networks 10. Natural Language Processing 11. Machine Learning Libraries 12. Optimizing Neural Networks for Mobile Devices 13. Best Practices

Understanding users emotions


While voice input is undoubtedly a useful feature, we all well know how the actual meaning of the sentence can be opposite to the literal one, depending on the speaker's intonation, facial expression, and context. Try this simple sentence: Oh, really? Depending on the conditions, this can mean: I doubt, I didn't know, I'm impressed, I don't care, This is obvious, and so on. The problem is that speech is not the only mode of conversation for human beings, and that's why much research is focused these days on teaching computers to understand (and also simulate) gestures, facial expressions, sentiments in a text, eye movements, sarcasm, and other affect manifestations. An interdisciplinary field that emerges around the question of emotional and compassionate AI is known as affective computing. It integrates knowledge from the computer and cognitive sciences, as well as psychology and robotics. The aim is the creation of computer systems that will adapt themselves...

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