Practical Machine Learning
Completed by Javier Eslava Schmalbach
August 12, 2018
8 hours (approximately)
Javier Eslava Schmalbach'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: Supervised Learning
- Category: Classification Algorithms
- Category: Machine Learning Algorithms
- Category: Predictive Modeling
- Category: R Programming
- Category: Model Evaluation
- Category: Applied Machine Learning
- Category: Random Forest Algorithm
- Category: Data Preprocessing
- Category: Classification And Regression Tree (CART)
- Category: Model Training
- Category: Machine Learning
