Hands-On Machine Learning with R - GitHub Pages
Feb 1, 2020 · This book provides hands-on modules for many of the most common machine learning methods to include: and more! You will learn how to build and tune these various models with R packages that have been tested and approved due to their ability to scale well.
Your First Machine Learning Project in R Step-By-Step
Feb 2, 2016 · In this step-by-step tutorial you will: Download and install R and get the most useful package for machine learning in R. Load a dataset and understand it's structure using statistical summaries and data visualization.
Machine Learning Mastery With R
Machine Learning Mastery with R is a great book for anyone looking to get started with machine learning. The book gives details how each step of a machine learning project should go: from descriptive statistics, to model selection and tuning, to predictions.
Machine Learning with R - Second Edition - GitHub
Harness the power of R to build common machine learning algorithms with real-world data science applications. Get to grips with R techniques to clean and prepare your data for analysis, and visualize your results.
Machine Learning in R for beginners - DataCamp
Nov 20, 2018 · This small tutorial is meant to introduce you to the basics of machine learning in R: more specifically, it will show you how to use R to work with the well-known machine learning algorithm called “KNN” or k-nearest neighbors.
Machine Learning with R - Google Books
Apr 15, 2019 · 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 with R - Fourth Edition - O'Reilly Media
Learn the end-to-end process of machine learning from raw data to implementation. Classify important outcomes using nearest neighbor and Bayesian methods. Predict future events using decision trees, rules, and support vector machines. Forecast numeric data and estimate financial values using regression methods.
This book provides hands-on modules for many of the most common machine learning methods to include: • Generalized low rank models • Clustering algorithms • Autoencoders • Regularized models • Random forests • Gradient boosting machines • Deep neural networks • Stacking / super learners • and more!
Machine Learning with R - Third Edition - O'Reilly Media
Harness the power of R to build flexible, effective, and transparent machine learning models. Learn quickly with a clear, hands-on guide by experienced machine learning teacher and practitioner, Brett Lantz.
PacktPublishing/Machine-Learning-with-R-Third-Edition
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.