Artificial Intelligence in Finance: A Python-Based Guide (Record no. 98805)

MARC details
000 -LEADER
fixed length control field 02322 a2200181 4500
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fixed length control field 241125b |||||||| |||| 00| 0 eng d
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9789385889233
082 ## - DEWEY DECIMAL CLASSIFICATION NUMBER
Classification number 001.64
Cutter HI:L
100 ## - MAIN ENTRY--PERSONAL NAME
Personal name Hilpisch Yves
245 ## - TITLE STATEMENT
Title Artificial Intelligence in Finance: A Python-Based Guide
250 ## - EDITION STATEMENT
Edition statement 1st Ed
260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT)
Name of publisher, distributor, etc O'Reilly
Date of publication, distribution, etc 2020
Place of publication, distribution, etc India
300 ## - PHYSICAL DESCRIPTION
Extent 480
520 ## - Remark
Summary, etc All Indian Reprints of O'Reilly are printed in Grayscale.<br/>The widespread adoption of AI and machine learning is revolutionizing many industries today. Once these technologies are combined with the programmatic availability of historical and real-time financial data, the financial industry will also change fundamentally. With this practical book, you'll learn how to use AI and machine learning to discover statistical inefficiencies in financial markets and exploit them through algorithmic trading.<br/><br/>Author Yves Hilpisch shows practitioners, students, and academics in both finance and data science practical ways to apply machine learning and deep learning algorithms to finance. Thanks to lots of self-contained Python examples, you'll be able to replicate all results and figures presented in the book.<br/><br/>In five parts, this guide helps you:<br/><br/>Learn central notions and algorithms from AI, including recent breakthroughs on the way to artificial general intelligence (AGI) and superintelligence (SI)<br/>Understand why data-driven finance, AI, and machine learning will have a lasting impact on financial theory and practice<br/>Apply neural networks and reinforcement learning to discover statistical inefficiencies in financial markets<br/>Identify and exploit economic inefficiencies through backtesting and algorithmic trading--the automated execution of trading strategies<br/>Understand how AI will influence the competitive dynamics in the financial industry and what the potential emergence of a financial singularity might bring about.<br/><br/>Source: https://www.amazon.in/Artificial-Intelligence-Finance-Python-Based-Grayscale/dp/9385889230/ref=sr_1_1?crid=1LG8P4BQRDSJM&dib=eyJ2IjoiMSJ9.1ew7hcrMzbu2W6DY20mYZg.ot5z5xKi98GUDbgS9FeijVvKjQ_1i_8WNNtZUdz_QXg&dib_tag=se&keywords=9789385889233&qid=1732521686&sprefix=9798986924021%2Caps%2C207&sr=8-1
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Artificial Intelligence
906 ## - LOCAL DATA ELEMENT F, LDF (RLIN)
a Information Technology
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Item type Book
Source of classification or shelving scheme Dewey Decimal Classification
Holdings
Withdrawn status Lost status Source of classification or shelving scheme Damaged status Not for loan Collection code Home library Current library Shelving location Date acquired Source of acquisition Cost, normal purchase price Collection Type Full call number Barcode Date last seen Cost, replacement price Koha item type
    Dewey Decimal Classification     Reference book Main Library Main Library Information Technology 28/10/2024 Shroff Publishers 1680.00 Foreign Book 001.64 HIL 119573 28/10/2024 2100.00 Book

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