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: Random Forest Algorithm
- Category: Classification And Regression Tree (CART)
- Category: Statistics
- Category: Supervised Learning
- Category: Predictive Modeling
- Category: Classification Algorithms
- Category: Decision Tree Learning
- Category: Artificial Neural Networks
- Category: Machine Learning Algorithms
- Category: Unsupervised Learning
- Category: Artificial Intelligence and Machine Learning (AI/ML)
- Category: Applied Machine Learning
