Applied Machine Learning Models: From Data to Decisions: Unlock 35+ Structured Workflows, Error-Reduction Techniques, and Deployment Frameworks to Deliver Measurable Business Impact
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Applied Machine Learning Models: From Data to Decisions: Unlock 35+ Structured Workflows, Error-Reduction Techniques, and Deployment Frameworks to Deliver Measurable Business Impact

by Omar Soub

Data Science business analytics MLOps Applied Machine Learning
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Applied Machine Learning Models offers a structured path from data to decisions. With more than 35 workflows, error-reduction techniques, and deployment frameworks, it focuses on applying machine learning in ways that support reliable outcomes and measurable business impact.

About This Book

Applied Machine Learning Models focuses on moving from data to decisions through practical machine learning workflows.

The book presents more than 35 structured workflows for organizing model development and application.

It also addresses error-reduction techniques intended to improve the reliability of machine learning results.

Deployment frameworks connect models with practical implementation and measurable business impact.

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I will be using this book for: