Building Intelligent Systems using Machine Learning
"This book is different. The author goes way beyond the theories and models to help simplify the complexities in building, measuring and managing complete large scale intelligent systems."
All the concepts you need to succeed with Machine Learning in practice.
What they are, what they are good for, and how to set one up for success.
Achieve your goals, mitigate mistakes, and produce data to improve over time.
Key concepts for how to execute, manage, and measure Intelligent Systems in practice.
Reliably use a variety of approaches, particularly machine learning.
Bring the parts together throughout your system's life cycle to achieve the impact you want.
Machine learning architects go beyond asking 'can I model that?' instead asking 'should my orginization model that?' This book gives you the conceptual understanding to take that leap.
"This is the first Systems Engineering text which gives the success factors for creating an Internet or Major Engineering project to deliver human experiences based upon AI and Machine Learning. This book is immensely practical and necessary."
"If you're looking to understand how to build & ship intelligence into your products, this book will give you a roadmap to do that. I highly recommend for PMs and engineering managers especially."
"This book explains ... with lots of concrete examples and very clear explanations about each and every step required to deliver a successful intelligent experience. ... I also really liked the tone of the book, full of funny examples and witty remarks."
Machine Learning in Production / AI Engineering.
Machine Learning: algorithms, modeling and engineering.
CSCE 585 - Machine Learning Systems: AI in production.
EBC4255 - Machine Learning for smart services.
Building Intelligent Systems is about Machine Learning Systems. It does not teach machine learning algorithms or machine learning math. Here are some great references for those topics: