- Predictive Analytics
- Data Processing
- Regression Analysis
- Machine Learning
- Machine Learning Algorithms
- Classification And Regression Tree (CART)
- R Programming
- Supervised Learning
- Feature Engineering
- Predictive Modeling
- Applied Machine Learning
- Random Forest Algorithm
Practical Machine Learning
Completed by Kevin Gerard Wunderlich
February 11, 2017
8 hours (approximately)
Kevin Gerard Wunderlich's account is verified. Coursera certifies their successful completion of Practical Machine Learning
What you will learn
Use the basic components of building and applying prediction functions
Understand concepts such as training and tests sets, overfitting, and error rates
Describe machine learning methods such as regression or classification trees
Explain the complete process of building prediction functions
Skills you will gain
