Focusing on practical application, this book guides readers through the entire process of creating machine learning applications, from conception to deployment. It is structured in four parts: planning and success measurement, building a working model, improving that model, and finally, deployment and monitoring strategies. With contributions from industry leaders and hands-on examples, it equips data scientists, software engineers, and product managers with essential skills, tools, and best practices for real-world ML projects.
