- Classification Algorithms
- Machine Learning
- Predictive Analytics
- Supervised Learning
- Model Evaluation
- Random Forest Algorithm
- Statistical Machine Learning
- Exploratory Data Analysis
- Data Preprocessing
- Regression Analysis
- Data Wrangling
- Feature Engineering
Practical Machine Learning
Completed by LIM CHONG YAN
February 18, 2020
8 hours (approximately)
LIM CHONG YAN '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
