null
Loading... Please wait...
FREE SHIPPING on All Unbranded Items LEARN MORE
Print This Page

Advances in Financial Machine Learning

List Price: $54.99
SKU:
9781119482086
Quantity:
Minimum Purchase
25 unit(s)
  • Availability: Confirm prior to ordering
  • Branding: minimum 50 pieces (add’l costs below)
  • Check Freight Rates (branded products only)

Branding Options (v), Availability & Lead Times

  • 1-Color Imprint: $2.00 ea.
  • Promo-Page Insert: $2.50 ea. (full-color printed, single-sided page)
  • Belly-Band Wrap: $2.50 ea. (full-color printed)
  • Set-Up Charge: $45 per decoration
FULL DETAILS
  • Availability: Product availability changes daily, so please confirm your quantity is available prior to placing an order.
  • Branded Products: allow 10 business days from proof approval for production. Branding options may be limited or unavailable based on product design or cover artwork.
  • Unbranded Products: allow 3-5 business days for shipping. All Unbranded items receive FREE ground shipping in the US. Inquire for international shipping.
  • RETURNS/CANCELLATIONS: All orders, branded or unbranded, are NON-CANCELLABLE and NON-RETURNABLE once a purchase order has been received.
  • Product Details

    Author:
    Marcos Lopez de Prado
    Format:
    Hardcover
    Pages:
    400
    Publisher:
    Wiley (February 21, 2018)
    Language:
    English
    Audience:
    General/trade
    ISBN-13:
    9781119482086
    Weight:
    26.4oz
    Case Pack:
    18
    File:
    Wiley-wileyUS_2_1_20260515-20260515.xml
    Folder:
    Wiley
    List Price:
    $54.99
    As low as:
    $52.24
    Publisher Identifier:
    P-WIL
    Discount Code:
    D
    Dimensions:
    6.3" x 9.2" x 1.2"
    Pub Discount:
    50
    Imprint:
    Wiley
    Country of Origin:
    United States
  • Overview

    Machine learning (ML) is changing virtually every aspect of our lives. Today ML algorithms accomplish tasks that until recently only expert humans could perform. As it relates to finance, this is the most exciting time to adopt a disruptive technology that will transform how everyone invests for generations. Readers will learn how to structure Big data in a way that is amenable to ML algorithms; how to conduct research with ML algorithms on that data; how to use supercomputing methods; how to backtest your discoveries while avoiding false positives. The book addresses real-life problems faced by practitioners on a daily basis, and explains scientifically sound solutions using math, supported by code and examples. Readers become active users who can test the proposed solutions in their particular setting. Written by a recognized expert and portfolio manager, this book will equip investment professionals with the groundbreaking tools needed to succeed in modern finance.