Machine Learning for Finance

Introducing the study of machine learning and deep learning algorithms for financial practitioners.
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Machine Learning for Finance

Jannes Klaas
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Introducing the study of machine learning and deep learning algorithms for financial practitioners.
This title is available to pre-order now and is expected to be published in
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Book Details

ISBN 139781789136364
Paperback300 pages

Book Description

Machine Learning for Finance is a guide for practitioners and students entering the fintech field. It shows how to solve some of the most common and pressing issues facing institutions in the financial industry, from retail banks to hedge funds. The book focuses on deep learning but also covers a range of other machine learning and analysis tools, such as NumPy, Matplotlib, and pandas. Machine Learning for Finance is packed full of hands-on code simulating many of the problems and providing working solutions. This book gives the reader confidence and the experience to go ahead and tackle real life problems.

The financial industry was an early adopter of computers and machine learning. Today, the industry is in a process of enormous change with nimble startups now serious competitors to centuries-old banks, and passive investing soaking up assets under management like a sponge. Meanwhile customers are expecting more performance, faster, and at a lower cost. The industry is adopting automatic, data driven algorithms at a rapid pace, and Machine Learning for Finance gives you skills you need to be at the forefront.

Table of Contents

What You Will Learn

  • Start building deep neural networks that can express uncertainty
  • Learn to make forecasts on time series with classic methods, such as Kalman filters, as well as new deep learning approaches
  • Get to know how generative models can help extract data and provide results even if little data is available
  • Gain insight into deploying models at scale and combating bias in models making sensitive decisions

Authors

Table of Contents

Book Details

ISBN 139781789136364
Paperback300 pages
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