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Applied Supervised Learning with R

You're reading from   Applied Supervised Learning with R Use machine learning libraries of R to build models that solve business problems and predict future trends

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Product type Paperback
Published in May 2019
Publisher
ISBN-13 9781838556334
Length 502 pages
Edition 1st Edition
Languages
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Authors (2):
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Jojo Moolayil Jojo Moolayil
Author Profile Icon Jojo Moolayil
Jojo Moolayil
Karthik Ramasubramanian Karthik Ramasubramanian
Author Profile Icon Karthik Ramasubramanian
Karthik Ramasubramanian
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Table of Contents (12) Chapters Close

Applied Supervised Learning with R
Preface
1. R for Advanced Analytics FREE CHAPTER 2. Exploratory Analysis of Data 3. Introduction to Supervised Learning 4. Regression 5. Classification 6. Feature Selection and Dimensionality Reduction 7. Model Improvements 8. Model Deployment 9. Capstone Project - Based on Research Papers Appendix

Docker


Docker is a simple tool that eases the process of developing, deploying, and executing software applications using containers. A container is analogous to a shipping industry container, and allows a developer to package an entire application with its dependencies, and ship it all out as one package. Once built on a system, the package will work on any other system as well, regardless of the differences in the infrastructure.

With Docker, we can create a single document (called a Dockerfile) that defines a simplified step for setting up the required environment for the application. The Dockerfile is then used to build a Docker image. A container is an instance of a Docker image. For the same application, we might sometimes have multiple containers that will help in load balancing for high-traffic applications.

Deploying the ML Model Using Docker and plumber

We will leverage the same plumber application with Docker for environment- and infrastructure-agnostic deployment. First, we will...

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