- Linear regression, Cost function, Gradient Descent, Normal equation
- Logistic regression, Classification, Multiclass classification(one vs all)
- Neural networks, Hidden layers
- Forward propagation, Backpropagation, Gradient Checking
- Evaluating a learning algorithm, Cross validation, Model selection, LR with Bias/Variance
- Support Vector Machines, Kernels
- K-Means Clustering (Unsupervised learning), Dimensionality Reduction with Principal Component Analysis
- Anomaly Detection, Gaussian distribution, Content based recommendations, Collaborative filtering
hakanmhmd / machine-learning Goto Github PK
View Code? Open in Web Editor NEWMachine Learning by Andrew Ng