- Regression Analysis
- Data Collection
- Data Processing
- Machine Learning
- Predictive Modeling
- R Programming
- Random Forest Algorithm
- Classification And Regression Tree (CART)
- Applied Machine Learning
- Feature Engineering
- Predictive Analytics
- Machine Learning Algorithms
Practical Machine Learning
Completed by Claudio A. DiMarco
February 29, 2020
8 hours (approximately)
Claudio A. DiMarco'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
