- Classification Algorithms
- Exploratory Data Analysis
- Data Preprocessing
- Regression Analysis
- Feature Engineering
- Predictive Analytics
- Predictive Modeling
- Machine Learning Algorithms
- Supervised Learning
- Model Evaluation
- Statistical Machine Learning
- Applied Machine Learning
Practical Machine Learning
Completed by Mark Andrew Rayfield
September 21, 2020
8 hours (approximately)
Mark Andrew Rayfield'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
