- R Programming
- Applied Machine Learning
- Model Evaluation
- Classification Algorithms
- Statistical Machine Learning
- Machine Learning
- Random Forest Algorithm
- Predictive Analytics
- Exploratory Data Analysis
- Data Preprocessing
- Supervised Learning
- Data Wrangling
Practical Machine Learning
Completed by DESNA SINGH
October 16, 2023
8 hours (approximately)
DESNA SINGH'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
