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Managing Machine Learning Projects

Gebonden Engels 2023 9781633439023
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Guide machine learning projects with the techniques in this unique project management guide. Managing Machine Learning Projects is a comprehensive guide to delivering successful machine learning projects from idea to production. The book is laid out as a series of fictionalised sprints that take you from pre-project requirements and proposal development all the way to deployment. You will discover battle-tested techniques for ensuring you have the appropriate data infrastructure, coordinating ML experiments, and measuring model performance. With this book as your guide, you will know how to bring a project to a successful conclusion, and how to use your lessons learned for future projects.
About the reader This book is for anyone interested in better management of machine learning projects. No technical skills are required!




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Over Simon Thompson

Simon Thompson is Professor of Logic and Computation in the Computing Laboratory of the University of Kent, where he has taught computing at undergraduate and postgraduate levels for the past twenty five years, and where he has been department head for the last six. His research work has centered on functional programming: program verification, type systems, and most recently development of software tools for functional programming languages. His team has built the HaRe tool for refactoring Haskell programs, and is currently developing Wrangler to do the same for Erlang. His research has been funded by various agencies including EPSRC and the European Framework programme. His training is as a mathematician: he has an MA in Mathematics from Cambridge and a D.Phil. in mathematical logic from Oxford. He has written three books in his field of interest; Type Theory and Functional Programming published in 1991; Miranda: The Craft of Functional Programming (1995) and Haskell: The Craft of Functional Programming (2nd ed. 1999). These are all published by Addison Wesley.

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