Machine Learning 2
- Number of features
- Linear regression
- Cost function
- Gradient descent
- Matrices
- Machine Learning - Multiple features
- Feature Scaling
- Gradient Descent - Learning Rate
- Features
- Polynomial Regression
- Normal Equation
- Multiple features
- Logistic regression (for classification)
- Multi-feature Classification (Iris)
- Kaggle - Melbourne housing listing
- Machine Learning Resources
- Regression Analyzis
- Classification Analysis
- Unbiased evaluation of a model
- Splitting data
- Model selection and validation
- K-fold valiadtion
- Learning Curves
- Hypermatameter tuning (optimization)
- The k-Nearest Neighbors (kNN)
- K-Means Clustering
- Boston housing prices
- Decision Tree
- Random Forrest
- Resnet 50