- Exploratory Data Analysis
- Data Wrangling
- Statistical Machine Learning
- Machine Learning Algorithms
- Applied Machine Learning
- Supervised Learning
- Feature Engineering
- Model Evaluation
- Data Preprocessing
- Predictive Analytics
- Machine Learning
- R Programming
Practical Machine Learning
Completed by MICHAEL L PASTOR
January 17, 2022
8 hours (approximately)
MICHAEL L PASTOR'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
