- Supervised Learning
- Predictive Analytics
- Data Processing
- Regression Analysis
- Classification And Regression Tree (CART)
- Machine Learning
- Data Collection
- Predictive Modeling
- Feature Engineering
- Random Forest Algorithm
- Applied Machine Learning
- Machine Learning Algorithms
Practical Machine Learning
Completed by Jordan Becker
March 6, 2017
8 hours (approximately)
Jordan Becker'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
