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Machine Learning for Healthcare Analytics Projectsaria expanded"true" class"a expander content a expander partial collapse content a expander content expanded" style'box sizing: border box; overflow: hidden; position: relative; color: rgb(15, 17, 17); font family: "Amazon Ember", Arial, sans serif; font size: 14px; padding bottom: 20px;' style"box sizing: border box; padding: 0px 0px 4px; margin: 0px; text rendering: optimizelegibility; font weight: 700; font size: 18px; line height: 24px;"Book
aria-expanded"true" class"a-expander-content a-expander-partial-collapse-content a-expander-content-expanded" style'box-sizing: border-box; overflow: hidden; position: relative; color: rgb(15, 17, 17); font-family: "Amazon Ember", Arial, sans-serif; font-size: 14px; padding-bottom: 20px;' style"box-sizing: border-box; padding: 0px 0px 4px; margin: 0px; text-rendering: optimizelegibility; font-weight: 700; font-size: 18px; line-height: 24px;"Book Description "box-sizing: border-box; padding: 0px; margin: 0px 0px 14px;"Machine Learning (ML) has changed the way organizations and individuals use data to improve the efficiency of a system. ML algorithms allow strategists to deal with a variety of structured, unstructured, and semi-structured data. Machine Learning for Healthcare Analytics Projects is packed with new approaches and methodologies for creating powerful solutions for healthcare analytics. "box-sizing: border-box; padding: 0px; margin: -4px 0px 14px;"This book will teach you how to implement key machine learning algorithms and walk you through their use cases employing a range of libraries from the Python ecosystem. You will build five end-to-end projects to evaluate the efficiency of Artificial Intelligence (AI) applications for carrying out simple-to-complex healthcare analytics tasks. With each project, you will gain new insights, which will then help you handle healthcare data efficiently. As you make your way through the book, you will use ML to detect cancer in a set of patients using support vector machines (SVMs) and k-Nearest neighbors (KNN) models. In the final chapters, you will create a deep neural network in Keras to predict the onset of diabetes in a huge dataset of patients. You will also learn how to predict heart diseases using neural networks. "box-sizing: border-box; padding: 0px; margin: -4px 0px 14px;" the end of this book, you will have learned how to address long-standing challenges, provide specialized solutions for how to deal with them, and carry out a range of cognitive tasks in the healthcare domain. style'box-sizing: border-box; padding: 0px 0px 4px; margin: 0px; text-rendering: optimizelegibility; font-weight: 700; font-size: 18px; line-height: 24px; color: rgb(15, 17, 17); font-family: "Amazon Ember", Arial, sans-serif;'Key FeaturesShipping Notes
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4.6 ★★★★★
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★★★★★ 5
Super fun!
Size: 8.5, Color: Red Pepper
These are so fantastic! The color is amazing! It is a bit on the tomato-red side of the color-wheel. The fit is great. They are comfortable from the 1st step. Easy to walk in.
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Reviewed in the United States on March 17, 2026
★★★★★ 5
Love them
Size: 5.5, Color: Red Pepper
I have gotten so many compliments on these shoes! They’re true to size and comfortable. Because of the material feet might sweat easier if hot but they dry quick. Quality is great and the color looks good, it’s more of a orange/red color. I got a 5.5 size
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Reviewed in the United States on May 21, 2026
★★★★★ 5
Stylist and comfortable!!!
Size: 6, Color: Red Pepper
So comfortable and well made. I’m going to get these in multiple colors.
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Reviewed in the United States on June 11, 2026
★★★★★ 2
Not sturdy enough for me
Size: 8, Color: Chestnut
Really cute and well made but not sturdy. I rolled my heel within minutes of walking around the house. Ain’t nobody got time for that
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Reviewed in the United States on May 6, 2026
★★★★★ 5
Oh so stylish Uggs
Size: 8, Color: Dense Smoke
They are so comfortable and stylish. I’m a size 8.5 and went with a size 8. Great value! Go get some I also got them in a tan color. Love them!
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Reviewed in the United States on May 18, 2026
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