23.6 Oz

Computers in Health Care Ser.: Aspects of the Computer-Based Patient Record…

In April 1991, the Institute of Medicine of the National Academy of Sciences completed an 18-month study on improving patient records in response to the need for better information management and increasing technologic advances. The conclusions and recommendations of this study have previously been described in a National Academy publication. This book is a collection of the background papers on which the conclusions and recommendations are based. Please review the photos for condition and thank you for looking.

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The trade paperback is written in English and spans 224 pages, providing valuable insights for professionals seeking to enhance their talent sourcing strategies.

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Designing Machine Learning Systems: An Iterative Process For Production-Rea…

Please refer to the section BELOW (and NOT ABOVE) this line for the product details – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – Title:Designing Machine Learning Systems: An Iterative Process For Production-Ready ApplicationsISBN13:9781098107963ISBN10:1098107969Author:Huyen, Chip (Author)Description:Many Tutorials Show You How To Develop Ml Systems From Ideation To Deployed Models But With Constant Changes In Tooling, Those Systems Can Quickly Become Outdated Without An Intentional Design To Hold The Components Together, These Systems Will Become A Technical Liability, Prone To Errors And Be Quick To Fall Apart In This Book, Chip Huyen Provides A Framework For Designing Real-World Ml Systems That Are Quick To Deploy, Reliable, Scalable, And Iterative These Systems Have The Capacity To Learn From New Data, Improve On Past Mistakes, And Adapt To Changing Requirements And Environments You? ???[ Ll Learn Everything From Project Scoping, Data Management, Model Development, Deployment, And Infrastructure To Team Structure And Business Analysis Learn The Challenges And Requirements Of An Ml System In Productionbuild Training Data With Different Sampling And Labeling Methodsleverage Best Techniques To Engineer Features For Your Ml Models To Avoid Data Leakageselect, Develop, Debug, And Evaluate Ml Models That Are Best Suit For Your Tasksdeploy Different Types Of Ml Systems For Different Hardwareexplore Major Infrastructural Choices And Hardware Designsunderstand The Human Side Of Ml, Including Integrating Ml Into Business, User Experience, And Team Structure Binding:Paperback, PaperbackPublisher:O’Reilly MediaPublication Date:2022-07-19Weight:0 lbsDimensions:Number of Pages:350Language:English

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