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Machine Learning for Finance

You're reading from Machine Learning for Finance Principles and practice for financial insiders

Product type Paperback

Published in May 2019

Publisher Packt

ISBN-13 9781789136364

Length 456 pages

Edition 1st Edition

Languages

Python

Tools

Scikit-learn

Concepts

Machine Learning

Authors (2):

Jannes Klaas

James Le

View More author details

Table of Contents (15) Chapters

Machine Learning for Finance

Contributors

Preface

Other Books You May Enjoy

1. Neural Networks and Gradient-Based Optimization FREE CHAPTER

2. Applying Machine Learning to Structured Data

3. Utilizing Computer Vision

4. Understanding Time Series

5. Parsing Textual Data with Natural Language Processing

6. Using Generative Models

7. Reinforcement Learning for Financial Markets

8. Privacy, Debugging, and Launching Your Products

9. Fighting Bias

10. Bayesian Inference and Probabilistic Programming

Index

Chapter 3. Utilizing Computer Vision

When Snapchat first introduced a filter featuring a breakdancing hotdog, the stock price of the company surged. However, investors were less interested in the hotdog's handstand; what actually fascinated them was that Snapchat had successfully built a powerful form of computer vision technology.

The Snapchat app was now not only able to take pictures, but it was also able to find the surfaces within those pictures that a hotdog could breakdance on. Their app would then stick the hotdog there, something that could still be done when the user moved their phone, allowing the hotdog to keep dancing in the same spot.

While the dancing hotdog may be one of the sillier applications of computer vision, it successfully showed the world the potential of the technology. In a world full of cameras, from the billions of smartphones, security cameras, and satellites in use every day, to Internet of Things (IoT) devices, being able to interpret images yields great benefits...

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Authors (2)

James Le

James Le

James Le is currently a master's student studying Computer Science at Rochester Institute of Technology. He is pursuing a research path in Computer Vision using Deep Learning. Moreover, he is an active freelance data scientist and data journalist, with specialties including machine/deep learning, recommendation systems, and data analysis/visualization.

See other products by James Le

Jannes Klaas

Jannes Klaas

Jannes Klaas is a quantitative researcher with a background in economics and finance. He taught machine learning for finance as lead developer for machine learning at the Turing Society, Rotterdam. He has led machine learning bootcamps and worked with financial companies on data-driven applications and trading strategies. Jannes is currently a graduate student at Oxford University with active research interests including systemic risk and large-scale automated knowledge discovery.

See other products by Jannes Klaas

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