- Data Preprocessing
- Classification Algorithms
- R Programming
- Supervised Learning
- Random Forest Algorithm
- Regression Analysis
- Applied Machine Learning
- Model Evaluation
- Data Wrangling
- Exploratory Data Analysis
- Machine Learning Algorithms
- Predictive Analytics
Practical Machine Learning
Completed by Konstantin Zuev
February 24, 2020
8 hours (approximately)
Konstantin Zuev'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
