Machine Learning in R: Repurpose Machine Learning Code for New Data

After watching the recent R tutorial videos on this channel, you might be wondering how you can apply or adapt the R code to your own data. In this video, I will show you how you can repurpose the R code from previous videos and apply it to model a new dataset. 🌟 Buy me a coffee: https://www.buymeacoffee.com/dataprofessor ⭕Data and Code: https://raw.githubusercontent.com/dataprofessor/data/master/dhfr.csv https://github.com/dataprofessor/code/tree/master/dhfr ⭕ Timeline 0:36 Launch RStudio or RStudio.cloud 0:43 Open iris-data-understanding.R file 0:48 Create a copy of iris-data-understanding.R 1:01 Save as dhfr-data-understanding.R 1:09 What is DHFR? 2:37 Load in DHFR data, type: library(datasets) and then data(dhfr) 5:00 Perform summary statistics 7:28 Use skimr package to explore the data 10:06 Make a scatter plot 11:55 Make a histogram 12:23 Make feature plots 15:26 Let's build the DHFR classification model 15:49 Load in the libraries 16:38 Set the seed for reproducibility 17:27 Build the training and CV models 18:05 Let's look at prediction results 19:51 Let's make Feature importance plots ⭕ Playlist: Check out our other videos in the following playlists. ✅ Data Science 101: https://bit.ly/dataprofessor-ds101 ✅ Data Science YouTuber Podcast: https://bit.ly/datascience-youtuber-podcast ✅ Data Science Virtual Internship: https://bit.ly/dataprofessor-internship ✅ Bioinformatics: http://bit.ly/dataprofessor-bioinformatics ✅ Data Science Toolbox: https://bit.ly/dataprofessor-datasciencetoolbox ✅ Streamlit (Web App in Python): https://bit.ly/dataprofessor-streamlit ✅ Shiny (Web App in R): https://bit.ly/dataprofessor-shiny ✅ Google Colab Tips and Tricks: https://bit.ly/dataprofessor-google-colab ✅ Pandas Tips and Tricks: https://bit.ly/dataprofessor-pandas ✅ Python Data Science Project: https://bit.ly/dataprofessor-python-ds ✅ R Data Science Project: https://bit.ly/dataprofessor-r-ds ⭕ Subscribe: If you're new here, it would mean the world to me if you would consider subscribing to this channel. ✅ Subscribe: https://www.youtube.com/dataprofessor?sub_confirmation=1 ⭕ Recommended Tools: Kite is a FREE AI-powered coding assistant that will help you code faster and smarter. The Kite plugin integrates with all the top editors and IDEs to give you smart completions and documentation while you’re typing. I've been using Kite and I love it! ✅ Check out Kite: https://www.kite.com/get-kite/?utm_medium=referral&utm_source=youtube&utm_campaign=dataprofessor&utm_content=description-only ⭕ Recommended Books: ✅ Hands-On Machine Learning with Scikit-Learn : https://amzn.to/3hTKuTt ✅ Data Science from Scratch : https://amzn.to/3fO0JiZ ✅ Python Data Science Handbook : https://amzn.to/37Tvf8n ✅ R for Data Science : https://amzn.to/2YCPcgW ✅ Artificial Intelligence: The Insights You Need from Harvard Business Review: https://amzn.to/33jTdcv ✅ AI Superpowers: China, Silicon Valley, and the New World Order: https://amzn.to/3nghGrd ⭕ Stock photos, graphics and videos used on this channel: ✅ https://1.envato.market/c/2346717/628379/4662 ⭕ Follow us: ✅ Medium: http://bit.ly/chanin-medium ✅ FaceBook: http://facebook.com/dataprofessor/ ✅ Website: http://dataprofessor.org/ (Under construction) ✅ Twitter: https://twitter.com/thedataprof/ ✅ Instagram: https://www.instagram.com/data.professor/ ✅ LinkedIn: https://www.linkedin.com/in/chanin-nantasenamat/ ✅ GitHub 1: https://github.com/dataprofessor/ ✅ GitHub 2: https://github.com/chaninlab/ ⭕ Disclaimer: Recommended books and tools are affiliate links that gives me a portion of sales at no cost to you, which will contribute to the improvement of this channel's contents. #dataprofessor #rdatascience #classificationmodel #datascienceproject #r #rtutorial #rworkshop #learnr #rprogramming #learnrprogramming #rcode #rstudio #rstudiocloud #datascience #datamining #bigdata #machinelearning #datascienceworkshop #dataminingworkshop #dataminingtutorial #datasciencetutorial #ai #artificialintelligence #supportvectormachine #svm #svminr #repurposecode #adaptcode #applycode #improvisecode