This programming exercise was done as part of Coursera's Machine Learning Course (Stanford University), taught by Prof. Andrew Ng.
- Built a spam classifier for emails using Support Vector Machines
- Preprocessed and normalized emails in the dataset
- Implemented feature extraction to generate a feature vector for each email
- Trained the SVM for spam classification using a simplified version of the SMO (sequential minimal optimization) algorithm and computed training and test accuracy