Introduction To Machine Learning In Quantitative Finance, An (Advanced Textbooks In Mathematics)

Ni, Hao; Dong, Xin; Zheng, Jinsong; Yu, Guangxi

ISBN 10: 1786349647 / ISBN 13: 9781786349644

Verlag: WSPC (EUROPE), 2021

Fast Shipping - Good and clean conditions used book. Pages and cover are intact. Limited notes marks and highlighting may be present. May show signs of normal shelf wear and bends on edges. Item may be missing CDs or access codes. May include library marks. Bestandsnummer des Verkäufers ZWM.U3IS

Inhaltsangabe:

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 authors Provide a systematic and rigorous introduction to supervised, unsupervised and reinforcement learning by establishing essential definitions and theorems. Dive into various types of neural networks, including artificial nets, convolutional nets, recurrent nets and recurrent reinforcement learning. Summarize key contents of each section in the tables as a cheat sheet. Include ample examples of financial applications. Showcase how to tackle an exemplar ML project on financial data end-to-end. Provide a GitHub repository https://github.com/deepintomlf/mlfbook.git that contains supplementary Python codes of all methods/examples. Featured 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!

Über die Autorin bzw. den Autor: Charlotte y Peter Fiell son dos autoridades en historia, teoría y crítica del diseño y han escrito más de sesenta libros sobre la materia, muchos de los cuales se han convertido en éxitos de ventas. También han impartido conferencias y cursos como profesores invitados, han comisariado exposiciones y asesorado a fabricantes, museos, salas de subastas y grandes coleccionistas privados de todo el mundo. Los Fiell han escrito numerosos libros para TASCHEN, entre los que se incluyen 1000 Chairs, Diseño del siglo XX, El diseño industrial de la A a la Z, Scandinavian Design y Diseño del siglo XXI.

Bibliografische Details

Titel: Introduction To Machine Learning In ...
Verlag: WSPC (EUROPE)
Erscheinungsdatum: 2021
Einband: Softcover
Zustand: good