Top positive review
Good insights, covers many bases, but only in limited detail - a really solid starting point for the subject
17 May 2017
This is written by someone who has a good general knowledge about the field. It outlines financial instruments, processes, data sources and so on, and generally seems to get these details right - for example identifying the primary financial news data sources. It then looks at financial instruments, describing them and the market, and some of the trading strategies. For the actual algorithm side, it's basically a whistle-stop overview of a range of relevant techniques for building a system. If you don't already know a fair bit about machine learning, then this is hardly going to give you the full details you need, and if you think this is going to cover enough for actually building a market-leading algorithm, then you'll be disappointed.
What it is, however, is an excellent starting point which will point you in the right general direction for data, for approaches, for ways to evaluate your performance, and so on. There are hints and tips that should steer you in the right direction which match up well with the processes and expectations I've seen working in the finance sector. There are also plenty of references to other materials, so this can provide a platform for then deepening your knowledge from the overview given here into a more complete understanding.
It's perhaps a little elementary for my needs, and it's far from a cheap book given its relative brevity, but it is well written, insightful, and tries to cover as many pieces of information needed for delving into ML-based investment as possible without being too technical, expecting too much maths, or expecting too much starting knowledge about trading. As an overview and introductory book, it's definitely worth a read.