Trees, SVM and Unsupervised Learning
Completed by Andres Restrepo Rodriguez
December 1, 2023
12 hours (approximately)
Andres Restrepo Rodriguez's account is verified. Coursera certifies their successful completion of Trees, SVM and Unsupervised Learning
What you will learn
Describe the advantages and disadvantages of trees, and how and when to use them.
Apply SVMs for binary classification or K > 2 classes.
Analyze the strengths and weaknesses of neural networks compared to other machine learning algorithms, such as SVMs.
Skills you will gain
- Category: Machine Learning Algorithms
- Category: Supervised Learning
- Category: Dimensionality Reduction
- Category: Applied Mathematics
- Category: Machine Learning Methods
- Category: Artificial Neural Networks
- Category: Statistical Machine Learning
- Category: Applied Machine Learning
- Category: Decision Tree Learning
- Category: Unsupervised Learning
- Category: Model Evaluation
- Category: Statistics
