Feature Engineering - Introduction to Dplyr Part 4
Offered By: Data Science Dojo via YouTube
Course Description
Overview
Conclude the dplyr tutorial series with advanced feature engineering techniques using both dplyr and base R. Learn to impute missing values, create new columns based on existing data, and explore four methods for combining datasets. Master 'mutate' and 'transmute' functions in dplyr, as well as 'ifelse' in base R for data manipulation. Apply these skills to tackle a wide range of data manipulation tasks, solidifying your proficiency in using dplyr for efficient data processing and analysis. Access accompanying code examples, related R programming resources, and the full video series for comprehensive learning.
Syllabus
Feature Engineering | Introduction to dplyr Part 4
Taught by
Data Science Dojo
Related Courses
Data Science at Scale - Capstone ProjectUniversity of Washington via Coursera Feature Engineering for Improving Learning Environments
University of Texas Arlington via edX How to Win a Data Science Competition: Learn from Top Kagglers
Higher School of Economics via Coursera Advanced Machine Learning
The Open University via FutureLearn Feature Engineering
Google Cloud via Coursera