Machine learning (ML) is a hot yet daunting topic. It’s perhaps the most important technological advancement supporting the revolution in artificial intelligence (AI), and most leading IT companies have been extracting value from it for some time. Almost every time predictions are made by a computer, like when a product or really anything is recommended, ML is at work. This book explains in technical detail how to get ML projects out of theory and into production.
ML is probabilistic by nature; that is, in contrast to traditional computer algorithms that are deterministic, ML (and AI) can produce different results with the same input. This is at the same time scary and enthralling. It mimics the creativity we’ve long associated most with human intelligence. AI has extracted its value and brought ML to the masses.
Since I work in web software development, I’m never going to become an ML engineer, but as a leader, I wanted to understand the key concepts better. This book explains those clearly, but a lot of the technical details went in one ear and out the other! For those more interested in ML’s AI applications, I suggest her follow-up book AI Engineering.
From what I understand, this book is one of the best one-volume introductions to understanding ML, and its clarity and comprehensiveness makes me see why. Chip Huyen has clearly spent a lot of time in the literature and in front of a computer understanding the technology. This work spans the academic-practitioner divide well and has found a welcoming audience in classrooms and in industry. If you’re looking to understand ML with some technical muscle to back it up, your search should stop here.
Designing Machine Learning Systems: An Iterative Process for Production-Ready Applications
By Chip Huyen
Narrated by Kathleen Li
Text copyright (c) 2022
O’Reilly Media
Audio copyright (c) 2025
Ascent Audio
ASIN B0DX2LXFZF
Length: 12:55
Genre: Artificial Intelligence
www.amazon.com