Trees, SVM and Unsupervised Learning
Completed by Hoi Yan Yu
November 3, 2024
12 hours (approximately)
Hoi Yan Yu'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: Unsupervised Learning
- Category: Machine Learning Methods
- Category: Model Evaluation
- Category: Supervised Learning
- Category: Applied Machine Learning
- Category: Statistical Machine Learning
- Category: Decision Tree Learning
- Category: Classification Algorithms
- Category: Random Forest Algorithm
- Category: Predictive Modeling
- Category: Applied Mathematics
- Category: Dimensionality Reduction
