- Data Wrangling
- Random Forest Algorithm
- R Programming
- Predictive Modeling
- Model Evaluation
- Feature Engineering
- Machine Learning
- Applied Machine Learning
- Classification Algorithms
- Supervised Learning
- Data Preprocessing
- Machine Learning Algorithms
Practical Machine Learning
Completed by Robert William Jeong
October 12, 2017
8 hours (approximately)
Robert William Jeong'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
