- Unsupervised Learning
- Advanced Analytics
- Applied Machine Learning
- Decision Tree Learning
- Random Forest Algorithm
- Supervised Learning
- Data Validation
- Machine Learning
- Workflow Management
- Feature Engineering
- Data Ethics
- Performance Tuning
The Nuts and Bolts of Machine Learning
Completed by Christian Reynolds
May 24, 2024
34 hours (approximately)
Christian Reynolds's account is verified. Coursera certifies their successful completion of The Nuts and Bolts of Machine Learning
What you will learn
Identify characteristics of the different types of machine learning
Prepare data for machine learning models
Build and evaluate supervised and unsupervised learning models using Python
Demonstrate proper model and metric selection for a machine learning algorithm
Skills you will gain
