About this book
The Hitchhikers Guide to Responsible Machine Learning is a delightful read. I had to flip from comic to comic first, which is fun and also on point about not falling into a pit of errors when doing machine learning with data. The detailed text explanations and beautifully constructed margin figures provide filling to the sandwich. Congratulations to Przemek, Anna and Aleksander for a creative and insightful contribution to the explainable AI literature.
Data science requires knowledge of the data and the methods to parse such data. A new kid on the analytical block is gaining popularity among data scientists: machine learning. It is powerful as it combines long-standing statistical methods with computational versatility. But as as the ‘Peter Parker principle’ goes ‘with great power comes great responsibility’. Biecek’s textbook provides a concise tutorial on how to tame the power of machine learning responsibly. This textbook needs to be read by anyone daring to tickle the power of machine learning.
This book is a short but illuminating and entertaining trip to responsible machine learning, in which accurate explanations of some fundamental concepts successfully mingle with a~pleasant, richly illustrated storyline. In a tourist-friendly manner it points out some important aspects of inference from the data and gives you a glimpse of how data driven answers are (or at least should be) obtained. Note that no professional travelling equipment is required - an open mind and a solid high-school level of mathematical abilities will certainly suffice. Needless to say, finishing this tour won’t make you an expert in data science - a vast and fascinating field which can be compared to a journey of a thousand miles.
But we all know that such journeys begin with a single step… or a hitchhiker’s guide!
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