In today's world, we are increasingly exposed to the words 'machine
learning' (ML), a term which sounds like a panacea designed to cure all
problems ranging from image recognition to machine language translation.
Over the past few years, ML has gradually permeated the financial
sector, reshaping the landscape of quantitative finance as we know it.An
Introduction to Machine Learning in Quantitative Finance aims to
demystify ML by uncovering its underlying mathematics and showing how to
apply ML methods to real-world financial data. In this book the
authorsFeatured with the balance of mathematical theorems and practical
code examples of ML, this book will help you acquire an in-depth
understanding of ML algorithms as well as hands-on experience. After
reading An Introduction to Machine Learning in Quantitative Finance, ML
tools will not be a black box to you anymore, and you will feel
confident in successfully applying what you have learnt to empirical
financial data!