Map/Reduce implementations of common ML algorithms

Jupyter notebooks that cover how to implement from scratch different ML algorithms (ordinary least squares, gradient descent, k-means, alternating least squares), using Python NumPy, and how to then make these implementations scalable using Map/Reduce and Spark.