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Building Machine Learning Powered Applications book cover

Building Machine Learning Powered Applications

Going from Idea to Product

Emmanuel Ameisen

This hands-on guide teaches you how to design, build, and deploy machine learning (ML) powered applications, from initial idea to deployed product. With code snippets, illustrations, and screenshots, you'll learn key ML concepts and tools for building real-world applications. This book is perfect for data scientists, software engineers, and product managers with little or no ML experience, who want to learn the process step-by-step. You'll discover how to plan and measure success, build a working ML model, improve performance, and deploy and monitor models in a production environment.
Publish Date
2020-02-11T00:00:00.000Z
2020-02-11T00:00:00.000Z
Goodreads Rating
4.2
ISBN
9781492045113
Recommendations
1
Recommendations
2020-05-12T00:10:54.000Z
Before starting to code an ML algorithm, spend one hour trying to do its job. Be the algorithm. Learned this early on from @IBMResearch's Salim Roukos. You can read more in the @mlpowered book, which is full of practical ML advice missing from textbooks:      source