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Machine Learning with R

Machine Learning with R

By : Brett Lantz
4.2 (46)
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Machine Learning with R

Machine Learning with R

4.2 (46)
By: Brett Lantz

Overview of this book

Machine learning, at its core, is concerned with transforming data into actionable knowledge. R offers a powerful set of machine learning methods to quickly and easily gain insight from your data. Machine Learning with R, Third Edition provides a hands-on, readable guide to applying machine learning to real-world problems. Whether you are an experienced R user or new to the language, Brett Lantz teaches you everything you need to uncover key insights, make new predictions, and visualize your findings. This new 3rd edition updates the classic R data science book to R 3.6 with newer and better libraries, advice on ethical and bias issues in machine learning, and an introduction to deep learning. Find powerful new insights in your data; discover machine learning with R.
Table of Contents (16 chapters)
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Index

Chapter 3. Lazy Learning – Classification Using Nearest Neighbors

A curious type of dining experience has appeared in cities around the world. Patrons are served in a completely darkened restaurant by waiters who move via memorized routes, using only their senses of touch and sound. The allure of these establishments is the belief that depriving oneself of sight will enhance the senses of taste and smell, and foods will be experienced in new ways. Each bite provides a sense of wonder while discovering the flavors the chef has prepared.

Can you imagine how a diner experiences the unseen food? Upon first bite, the senses are overwhelmed. What are the dominant flavors? Does the food taste savory or sweet? Does it taste similar to something eaten previously? Personally, I imagine this process of discovery in terms of a slightly modified adage—if it smells like a duck and tastes like a duck, then you are probably eating duck.

This illustrates an idea...

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