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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

2. Applying Machine Learning to Structured Data FREE CHAPTER

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

Seq2seq models

In 2016, Google announced that it had replaced the entire Google Translate algorithm with a single neural network. The special thing about the Google Neural Machine Translation system is that it translates mutliple languages "end-to-end" using only a single model. It works by encoding the semantics of a sentence and then decoding the semantics into the desired output language.

The fact that such a system is possible at all baffled many linguists and other researchers, as it shows that machine learning can create systems that accurately capture high-level meanings and semantics without being given any explicit rules.

These semantic meanings are represented as an encoding vector, and while we don't quite yet know how to interpret these vectors, there are a lot of useful applications for them. Translating from one language to another is one such popular method, but we could use a similar approach to "translate" a report into a summary. Text summarization has made great strides...

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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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