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Construct extremely safe and scalable machine studying platforms to assist the fast-paced adoption of machine studying options
Key Options:
Discover totally different ML instruments and frameworks to unravel large-scale machine studying challenges within the cloudBuild an environment friendly information science surroundings for information exploration, mannequin constructing, and mannequin trainingLearn methods to implement bias detection, privateness, and explainability in ML mannequin improvement
E-book Description:
With a extremely scalable machine studying (ML) platform, organizations can shortly scale the supply of ML merchandise for sooner enterprise worth realization, so there’s a enormous demand for expert ML options architects in numerous industries. This hands-on ML e book takes you thru the design patterns, architectural concerns, and the most recent expertise that you’ll want to know to change into a profitable ML options architect.
You may begin by understanding ML fundamentals and the way ML may be utilized to real-world enterprise issues. As soon as you have explored among the main ML algorithms for fixing several types of issues, the e book will make it easier to familiarize yourself with information administration and utilizing ML libraries reminiscent of TensorFlow and PyTorch. You may discover ways to use open supply expertise reminiscent of Kubernetes/Kubeflow to construct a knowledge science surroundings and ML pipelines after which advance to constructing an enterprise ML structure utilizing Amazon Net Companies (AWS) companies. You may then cowl safety and governance concerns, superior ML engineering strategies, and methods to apply bias detection, explainability, and privateness in ML mannequin improvement. Lastly, you will get acquainted with AWS AI companies and their purposes in real-world use instances.
By the tip of this e book, you’ll design and construct an ML platform to assist widespread use instances and structure patterns.
What You Will Study:
Apply ML methodologies to unravel enterprise problemsDesign a sensible enterprise ML platform architectureImplement MLOps for ML workflow automationBuild an end-to-end information administration structure utilizing AWSTrain large-scale ML fashions and optimize mannequin inference latencyCreate a enterprise software utilizing an AI service and a customized ML modelUse AWS companies to detect information and mannequin bias and clarify fashions
Who this e book is for:
This e book is for information scientists, information engineers, cloud architects, and machine studying fans who need to change into machine studying options architects. Fundamental data of the Python programming language, AWS, linear algebra, likelihood, and networking ideas is assumed.
Writer : Packt Publishing
Publication date : Jan. 21 2022
Language : English
Print size : 442 pages
ISBN-10 : 1801072167
ISBN-13 : 978-1801072168
Merchandise weight : 753 g
Dimensions : 19.05 x 2.54 x 23.5 cm
Greatest Sellers Rank: #1,169,437 in Books (See Prime 100 in Books) #156 in Machine Idea #278 in AI Idea of Computing #522 in Pc Science Modelling & Simulation
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