Practical Machine Learning
Completed by Daniel Kiskis
November 5, 2017
8 hours (approximately)
Daniel Kiskis'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: Machine Learning Methods
- Category: Random Forest Algorithm
- Category: Classification And Regression Tree (CART)
- Category: Data Preprocessing
- Category: Supervised Learning
- Category: Predictive Modeling
- Category: Machine Learning Software
- Category: Regression Analysis
- Category: Feature Engineering
- Category: Machine Learning Algorithms
- Category: Classification Algorithms
- Category: Model Evaluation
