Machine Learning and Data Science Blueprints for Finance

Machine Learning and Data Science Blueprints for Finance: From Building Trading Strategies to Robo-Advisors Using Python

eBook Details:

  • Paperback: 432 pages
  • Publisher: WOW! eBook (November 10, 2020)
  • Language: English
  • ISBN-10: 1492073059
  • ISBN-13: 978-1492073055

eBook Description:

Machine Learning and Data Science Blueprints for Finance: From Building Trading Strategies to Robo-Advisors Using Python

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).

This book covers:

  • Supervised learning regression-based models for trading strategies, derivative pricing, and portfolio management
  • Supervised learning classification-based models for credit default risk prediction, fraud detection, and trading strategies
  • Dimensionality reduction techniques with case studies in portfolio management, trading strategy, and yield curve construction
  • Algorithms and clustering techniques for finding similar objects, with case studies in trading strategies and portfolio management
  • Reinforcement learning models and techniques used for building trading strategies, derivatives hedging, and portfolio management
  • NLP techniques using Python libraries such as NLTK and scikit-learn for transforming text into meaningful representations

Ideal for professionals working at hedge funds, investment and retail banks, and fintech firms, this Machine Learning and Data Science Blueprints for Finance 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.

DOWNLOAD

2 Responses

  1. October 6, 2020

    […] and Machine Learning for Coders: A Programmer’s Guide to Artificial […]

  2. October 19, 2020

    […] Machine Learning Design Patterns: Solutions to Common Challenges in Data Preparation, Model Building, and MLOps […]

Leave a Reply

Your email address will not be published. Required fields are marked *

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.