- Supervised Learning
- Classification And Regression Tree (CART)
- Data Collection
- Applied Machine Learning
- Machine Learning Algorithms
- Feature Engineering
- Machine Learning
- Predictive Analytics
- R Programming
- Data Processing
- Regression Analysis
- Random Forest Algorithm
Practical Machine Learning
Completed by Gautam Amin
February 4, 2016
8 hours (approximately)
Gautam Amin'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
