9781119522195-1119522196-Big Data and Machine Learning in Quantitative Investment (Wiley Finance)

Big Data and Machine Learning in Quantitative Investment (Wiley Finance)

ISBN-13: 9781119522195
ISBN-10: 1119522196
Edition: 1
Author: Tony Guida
Publication date: 2019
Publisher: Wiley
Format: Hardcover 304 pages
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Book details

ISBN-13: 9781119522195
ISBN-10: 1119522196
Edition: 1
Author: Tony Guida
Publication date: 2019
Publisher: Wiley
Format: Hardcover 304 pages

Summary

Big Data and Machine Learning in Quantitative Investment (Wiley Finance) (ISBN-13: 9781119522195 and ISBN-10: 1119522196), written by authors Tony Guida, was published by Wiley in 2019. With an overall rating of 4.1 stars, it's a notable title among other Finance (Investing, Data Mining, Databases & Big Data, Data Processing) books. You can easily purchase or rent Big Data and Machine Learning in Quantitative Investment (Wiley Finance) (Hardcover) from BooksRun, along with many other new and used Finance books and textbooks. And, if you're looking to sell your copy, our current buyback offer is $0.62.

Description

Get to know the ‘why’ and ‘how’ of machine learning and big data in quantitative investment

Big Data and Machine Learning in Quantitative Investment is not just about demonstrating the maths or the coding. Instead, it’s a book by practitioners for practitioners, covering the questions of why and how of applying machine learning and big data to quantitative finance.

The book is split into 13 chapters, each of which is written by a different author on a specific case. The chapters are ordered according to the level of complexity; beginning with the big picture and taxonomy, moving onto practical applications of machine learning and finally finishing with innovative approaches using deep learning.

• Gain a solid reason to use machine learning

• Frame your question using financial markets laws

• Know your data

• Understand how machine learning is becoming ever more sophisticated

Machine learning and big data are not a magical solution, but appropriately applied, they are extremely effective tools for quantitative investment ― and this book shows you how.

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