Machine Learning and Data Science Blueprints for Finance: From Building Trading Strategies To Robo-advisors Using Python (1)

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Synopsis
Over the next few decades, machine learning and data science will transform the finance industry. With this practical book, analysts, traders, researchers, and developers will learn how to build machine learning algorithms crucial to the industry. You'll examine ML concepts and over 20 case studies in supervised, unsupervised, and reinforcement learning, along with natural language processing (NLP).Ideal for professionals working at hedge funds, investment and retail banks, and fintech firms, this book also delves deep into portfolio management, algorithmic trading, derivative pricing, fraud detection, asset price prediction, sentiment analysis, and chatbot development. You'll explore real-life problems faced by practitioners and learn scientifically sound solutions supported by code and examples.This book covers:Supervised learning regression-based models for trading strategies, derivative pricing, and portfolio managementSupervised learning classification-based models for credit default risk prediction, fraud detection, and trading strategiesDimensionality reduction techniques with case studies in portfolio management, trading strategy, and yield curve constructionAlgorithms and clustering techniques for finding similar objects, with case studies in trading strategies and portfolio managementReinforcement learning models and techniques used for building trading strategies, derivatives hedging, and portfolio managementNLP techniques using Python libraries such as NLTK and scikit-learn for transforming text into meaningful representations
Copyright:
2021

Book Details

Book Quality:
Publisher Quality
Book Size:
432 Pages
ISBN-13:
9781492073000
Related ISBNs:
9781492073024, 9781492073017, 9781492073055
Publisher:
O'Reilly Media
Date of Addition:
Copyrighted By:
Hariom Tatsat, Sahil Puri, Brad Lookabaugh
Adult content:
No
Language:
English
Has Image Descriptions:
No
Categories:
Nonfiction, Computers and Internet, Business and Finance
Submitted By:
Bookshare Staff
Usage Restrictions:
This is a copyrighted book.

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