Introduction to Data Science with R - Exploratory Modeling 2

Part 6 in a in-depth hands-on tutorial introducing the viewer to Data Science with R programming. The video provides end-to-end data science training, including data exploration, data wrangling, data analysis, data visualization, feature engineering, and machine learning. All source code from videos are available from GitHub.


☕ If you found this content useful and would like to support the channel, you can buy me a coffee: https://www.buymeacoffee.com/DaveOnData


★★★ My online data analysis courses ▶ https://school.daveondata.com


-----------------------------------------------------------------------------------------------------------------------
🤖 Looking for robust training in machine learning? 🤖
-----------------------------------------------------------------------------------------------------------------------
⚠ This video series is quite old now and incomplete. ⚠

👉 My new online course covers using tidymodels in R to do machine learning and covers everything you need to know (e.g., algorithms, math, bias-variance tradeoff, tuning, etc.).

Check out the following YouTube video to learn more:
📺 https://youtu.be/b6hiyLEFA_M



// THINGS HAVE CHANGED SINCE ORIGINAL VIDEO

⚠ - The data for the competition has changed since this video series was started. You can find the applicable .CSVs in the GitHub repo.

💻 GitHub: https://github.com/EasyD/IntroToDataScience


#DataScience #Rprogramming #RprogrammingForDataScience

#R (Progamming Language) #Data Science #Data Analysis #Feature Engineering #Visualization #Data Wrangling #Data Exploration #R Programming #R Programming Tutorial #R Programming Training #Data Science with R #Data Scientist #Machine Learning with R #Programming #Tutorial #Training #Data Science Training #Data Science Tutorial #Machine Learning #Data Visualization #Data Science with R Programming