This post is part of a series covering the exercises from Andrew Ng’s machine learning class on Coursera. The original code, exercise text, and data files for this post are available here.

Part 1 – Simple Linear Regression
Part 2 – Multivariate Linear Regression
Part 3 – Logistic Regression
Part 4 – Multivariate Logistic Regression
Part 5 – Neural Networks
Part 6 – Support Vector Machines
Part 7 – K-Means Clustering & PCA
Part 8 – Anomaly Detection & Recommendation

One of the pivotal moments in my professional development this year came when I discovered Coursera. I’d heard of the “MOOC” phenomenon but had not had the time to dive in and take a class. Earlier this year I finally pulled the trigger and signed up for Andrew Ng’s Machine Learning class. I completed the whole thing from start to finish, including all of the programming exercises. The experience opened my eyes to the power of this type of education platform, and I’ve been hooked ever since.

Source: Machine Learning Exercises In Python, Part 1

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