- Data Processing
- R Programming
- Predictive Analytics
- Machine Learning
- Data Collection
- Applied Machine Learning
- Classification And Regression Tree (CART)
- Feature Engineering
- Regression Analysis
- Random Forest Algorithm
- Machine Learning Algorithms
- Supervised Learning
Practical Machine Learning
Completed by Anna Opilat
November 4, 2020
8 hours (approximately)
Anna Opilat'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
