Learn the skills necessary to design, build, and deploy applications powered by machine learning (ML). Through the course of this hands-on book, youâ€Â(TM)ll build an example ML-driven application from initial idea to deployed product. Data scientists, software engineers, and product managersâ€Â"including experienced practitioners and novices alikeâ€Â"will learn the tools, best practices, and challenges involved in building a real-world ML application step by step.
Author Emmanuel Ameisen, an experienced data scientist who led an AI education program, demonstrates practical ML concepts using code snippets, illustrations, screenshots, and interviews with industry leaders. Part I teaches you how to plan an ML application and measure success. Part II explains how to build a working ML model. Part III demonstrates ways to improve the model until it fulfills your original vision. Part IV covers deployment and monitoring strategies.
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Emmanuel Ameisen has worked for years as a Data Scientist. He implemented and deployed predictive analytics and machine learning solutions for Local Motion and Zipcar. Recently, Emmanuel has led Insight Data Science's AI program where he oversaw more than a hundred machine learning projects. Emmanuel holds graduate degrees in artificial intelligence, computer engineering, and management from three of France's top schools.
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