Applied Machine Learning: Algorithms
Offered By: LinkedIn Learning
Course Description
Overview
Learn about common machine learning algorithms, their pros and cons, and develop hands-on skills to leverage them.
Syllabus
Introduction
- Applied machine learning: Algorithms
- What you should know
- K-means
- K evaluation
- Understanding clusters
- Other algorithms
- Challenge: Apply KNN
- Solution: Apply KNN
- PCA
- Structure of components
- Components
- Scatter plot
- Other algorithms
- Challenge: Utilize PCA
- Solution: Utilize PCA
- Linear regression algorithm
- scikit-learn
- Real-world example
- Assumptions
- Challenge: Develop a linear regression model
- Solution: Develop a linear regression model
- Logistic regression algorithm
- Basic example
- Assumptions
- Challenge: Construct a logistic regression model
- Solution: Construct a logistic regression model
- Decision tree algorithm
- Real-world example
- Random Forest and XGBoost
- Challenge: Design a decision tree model
- Solution: Design a decision tree model
- Next steps
Taught by
Derek Jedamski
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