No denying, I am proud of having come this far. This and another week to go before I can bring this course to a closure. Week 10 comprised of discussions on various flavors of Gradient Descent such as Stocastic and Mini-Batch Gradient Descent. We also worked through some of the big data processing techniques such as MapReduce and Online Learning.
Week 9 covered one of the most widespread applications of Machine Learning – Recommender Systems. These are the systems that churn business for e-commerce sites like Amazon and the streaming giant Netflix. Recommender systems take into consideration the past behaviors and decisions of their users and make recommendations of products and services that these users are likely to be interested in.
We also touched ground on Anomaly Detection algorithms which fish out outliers or anomalies from a dataset by running probability density analysis like Gaussians on the dataset.