sdsawtelle / andrew-ng-ml-hw-python

A collection of HW solutions for Andrew Ng's amazing ML course using Python with scikit-learn.

andrew-ng-ml-hw-python

A collection of Jupyter Notebooks where I solve the homeworks for Andrew Ng's wonderful, amazing, miraculous Machine Learning course but I do it in Python with Sci-kit learn rather than in MATLAB (open source FTW). This means I start from the data set provided for the homework and then I make the same plots, fit the same classes of algorithms and basically meet all the objectives of the homework.

Listing of Notebooks

The file machine-learning-course-notebook includes all my notes that I took while watching the lecture videos (along with screen-capping what I considered the most useful slides from his powerpoints).

The homework notebooks are as follows:

hw-wk2 - Linear Regression
hw-wk3 - Logistic Regression
hw-wk4 - Neural Networks
hw-wk6 - Bias-Variance, Learning Curves, Validation Curves
hw-wk7 - Support Vector Machines (SVM)
hw-wk7-spam-preprocessing and hw-wk7-spam-svm - Spam Classification with NLP and SVM
hw-wk8 - K-Means Clustering and Principle Component Analysis (PCA)
hw-wk9-anomaly - Anomaly Detection
hw-wk9-recommender - Recommender Systems