Book about design patterns specific to machine learning training and productionization. Design patterns are useful since they’re tried-and-tested solutions to reoccurring problems. Even though I’ve used ML in my work for several years, some of these patterns are still new to me. The book is aimed at ML practitioners in the industry and less towards…
Category: Data Science / ML
Fundamentals of Data Visualization by Claus O. Wilke (8.0/10)
Part 1: From Data to Visualization All figures should be reproducible from data and code, should not have to make manual adjustments in Illustrator, or you will be dissuaded from updating them, or you may forget how they’re generated. Figures may be “ugly” (aesthetically unpleasing), “bad” (unclear and confusing), or “wrong” (objectively incorrect). An aesthetic…
Designing Voice User Interfaces by Cathy Pearl (7.3/10)
Voice user interfaces like Siri and Alexa have improved in some ways, but in many other ways are similar to IVR phone systems from the 1970s. This book goes through various things to look out for while designing them. For example: Be as brief as possible and use visual mode to display lots of information….
The Book of Why by Judea Pearl (8.0/10)
Book by Judea Pearl, one of the leaders of causal inference who received a Turing award for inventing Bayesian networks. It has some equations, with a level of technicality somewhere between a typical popular science book and a textbook. Causal inference is required because it’s impossible to tell between causation and correlation from data alone,…
The Lady Tasting Tea by David Salsburg (8.3/10)
Tells the story of how statistics emerged as a scientific discipline in the 20th century. The title comes from an apocryphal story by Fisher describing an experiment to see if a lady can taste the difference between two ways of making tea. The book describes the lives and circumstances of the people involved, explains the…