Machine Learning course by Andrew Ng in coursera, adopted to Python
Ex.1 was divided into 2 segments: ex1_1 (Single variable Linear Regression) and ex1_2 (Multiple variables)
Ex.2 was divided into 2 segments: based on the 2 datasets in the exercise.
Ex.3 contains the Logistic Regression part of the matlab exercise.
Ex.4 contains the Neural-Network exercise in the 2nd part of Ex.3 (feed forward) and Ex.4 (backpropogation).
The file name is NN.py. There's also a Keras implementation and TF implementations.
Ex.5 contains all the of the exercise in the fily ex5_all.
Ex.6 - SVM was done with sklearn (file name: SVM.py). I plan to try and implement the SMO algorithm sometime later.
Ex.7 was divided into KMeans.py and PCA.py
Ex.8 was divided into 2 segments: ex8_1 (Anomaly Detection) and ex8_2 (Recommender Systems)