An introduction to machine learning in quantitative finance / (Record no. 97727)
[ view plain ]
| 000 -LEADER | |
|---|---|
| fixed length control field | 04487cam a2200469 i 4500 |
| 001 - CONTROL NUMBER | |
| control field | 000q0275 |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION | |
| fixed length control field | 200910s2021 si ob 001 0 eng d |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
| ISBN | 9781786349378 |
| -- | (ebook) |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
| -- | (hardback) |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
| -- | (paperback) |
| 082 00 - CLASSIFICATION NUMBER | |
| Call Number | 332.0285/631 |
| 100 1# - AUTHOR NAME | |
| Author | Ni, Hao |
| 245 13 - TITLE STATEMENT | |
| Title | An introduction to machine learning in quantitative finance / |
| 300 ## - PHYSICAL DESCRIPTION | |
| Number of Pages | 1 online resource (xxiv, 238 pages). |
| 490 1# - SERIES STATEMENT | |
| Series statement | Advanced textbooks in mathematics |
| 505 0# - FORMATTED CONTENTS NOTE | |
| Remark 2 | Preface -- About the authors -- Acknowledgments -- Disclaimer -- Listings -- Overview of machine learning and financial applications -- Supervised learning -- Linear regression and regularization -- Tree-based models -- Neural networks -- Cluster analysis -- Principal component analysis -- Reinforcement learning -- Case study in finance : home credit default risk -- Bibliography -- Index. |
| 520 ## - SUMMARY, ETC. | |
| Summary, etc | "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. Supplement Python codes of all the methods/examples in a GitHub repository. 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! The Python codes contained within An Introduction to Machine Learning in Quantitative Finance have been made publicly available on the author's GitHub: 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!"--Publisher's website. |
| 650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| General subdivision | Mathematical models. |
| 700 1# - AUTHOR 2 | |
| Author 2 | Dong, Xin, |
| 700 1# - AUTHOR 2 | |
| Author 2 | Zheng, Jinsong, |
| 700 1# - AUTHOR 2 | |
| Author 2 | Yu, Guangxi, |
| 856 40 - ELECTRONIC LOCATION AND ACCESS | |
| Uniform Resource Identifier | https://www.worldscientific.com/worldscibooks/10.1142/q0275#t=toc |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) | |
| Koha item type | eBooks |
| 264 #1 - | |
| -- | Singapore ; |
| -- | New Jersey : |
| -- | World Scientific, |
| -- | 2021. |
| 336 ## - | |
| -- | text |
| -- | txt |
| -- | rdacontent |
| 337 ## - | |
| -- | computer |
| -- | n |
| -- | rdamedia |
| 338 ## - | |
| -- | online resource |
| -- | nc |
| -- | rdacarrier |
| 650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Finance |
| 650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Machine learning. |
No items available.