Jared M Maruskin

Fundamentals of Data Science Part III Jared M Maruskin

In Part III of this series, we cover the fundamentals of machine learning, focusing on: validation methodology (reprint)nearest neighbor, k-means, support vector machines, principal component analysistree-based methods: decision trees, bagging, random forest, boosting, XGBoostartificial neural networks and deep learningreinforcement learning

The focus is on algorithmic development and programming. We code each technique from scratch in Python, using an object-oriented approach.