Practical Machine Learning
Completed by Daniel Stearns
May 30, 2016
8 hours (approximately)
Daniel Stearns'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
- Category: Predictive Analytics
- Category: Classification And Regression Tree (CART)
- Category: Applied Machine Learning
- Category: Regression Analysis
- Category: Classification Algorithms
- Category: Supervised Learning
- Category: Machine Learning Algorithms
- Category: Machine Learning Methods
- Category: Data Preprocessing
- Category: Feature Engineering
- Category: Model Training
- Category: Machine Learning
