5 reasons why you should get a copy of Machine Learning for Algorithmic Trading

I managed to get my hands on Stefan Jansen’s Machine Learning for Algorithmic Trading, and I highly recommend you to get it too.

Here’s why:

1. You’re reading from the minds of one of the top industry experts.

The author is the CEO of Applied AI, an online course provider in machine learning and AI.

With an extensive teaching and consulting experience in AI and data science, the author explains in a way that helps you to understand.

2. You are doing algorithmic trading.

You have already been doing algorithmic trading, it’s time to consider applying machine learning and deep learning strategies, if you haven’t.

If already have, this will be a good read on various applications you might never thought possible.

There’s also sections on NLP for sentiment analysis on alternative data, with Spacy and Textacy.

As the title suggests, the sections covered have a big picture focus on algorithmic trading. This is unlike most books I’ve come across with titles that tend to over-promise.

3. You want to learn deep learning and machine learning with more pictorial content.

Most books I’ve read on ML and DL are too dry per se, or have pages filled with equations that I can hardly follow.

This book takes a different approach. It’s filled with graphics, charts, and illustrations. All sentences are written directly in human-speak that explains the details.

Each chapter dives into specifics on the terminology and methodology.

4. You want a hands-on approach to ML and DL, with Python source codes.

Source codes are mainly in Jupyter format, and can be found in the official GitHub repository.

Throughout the book there’s also key sections of the source codes to help explain its use.

5. It’s bang for bucks given the quality of content.

With over 20 chapters and 800 pages, this is like a textbook for a full semester course on machine learning.

Disclaimer: I’ve been given a review copy of this book, and I think it’s good!

I apply machine learning and deep learning techniques as part of my research work on next-generation payment systems, and also performing studies with financial time series data during my free time. The contents in this book has helped me a lot with clear explanations and wide coverage of algos.

This is just a review of my thoughts on this book. You can get a copy too on Amazon.

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