Solutions to Andrew NG's machine learning course on Coursera
- EX1
- Implementing and visualizing linear regression using gradient descent as optimizer
- EX2
- Implementing and visualizing logistic regression using fminfunc as optimizer.
- EX3
- Implementing One vs All logistic regression to classify handwritten numbers.
- EX4
- Implementing a neural net with some pre trained weights on the same dataset as the previous problem using feedforward and backpropagation algorithm.
- EX5
- Learning and tuning hyperparameters such as lambda for regularization, via cross validation.
- EX6
- Implementing an linear SVM for random dataset using RBF(Radial Basis Function).