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Hands-On Machine Learning for Algorithmic Trading

You're reading from Hands-On Machine Learning for Algorithmic Trading Design and implement investment strategies based on smart algorithms that learn from data using Python

Product type Paperback

Published in Dec 2018

Publisher Packt

ISBN-13 9781789346411

Length 684 pages

Edition 1st Edition

Languages

Python

Tools

TensorFlow

Concepts

Design

Authors (2):

Jeffrey Yau

Stefan Jansen

View More author details

Table of Contents (23) Chapters

Preface

1. Machine Learning for Trading

2. Market and Fundamental Data FREE CHAPTER

3. Alternative Data for Finance

4. Alpha Factor Research

5. Strategy Evaluation

6. The Machine Learning Process

7. Linear Models

8. Time Series Models

9. Bayesian Machine Learning

10. Decision Trees and Random Forests

11. Gradient Boosting Machines

12. Unsupervised Learning

13. Working with Text Data

14. Topic Modeling

15. Word Embeddings

16. Deep Learning

17. Convolutional Neural Networks

18. Recurrent Neural Networks

19. Autoencoders and Generative Adversarial Nets

20. Reinforcement Learning

21. Next Steps

22. Other Books You May Enjoy

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Who this book is for

The book is for data analysts, data scientists, and Python developers, as well as investment analysts and portfolio managers working within the finance and investment industry. If you want to perform efficient algorithmic trading by developing smart investigating strategies using ML algorithms, this is the book you need! Some understanding of Python and ML techniques is mandatory.

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Authors (2)

Yau

Yau

See other products by Yau

Stefan Jansen

Stefan Jansen

Stefan is the founder and CEO of Applied AI. He advises Fortune 500 companies, investment firms, and startups across industries on data & AI strategy, building data science teams, and developing end-to-end machine learning solutions for a broad range of business problems. Before his current venture, he was a partner and managing director at an international investment firm, where he built the predictive analytics and investment research practice. He was also a senior executive at a global fintech company with operations in 15 markets, advised Central Banks in emerging markets, and consulted for the World Bank. He holds Master's degrees in Computer Science from Georgia Tech and in Economics from Harvard and Free University Berlin, and a CFA Charter. He has worked in six languages across Europe, Asia, and the Americas and taught data science at Datacamp and General Assembly.

See other products by Stefan Jansen

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