Kevin Markham. Introduction to machine learning with scikit-learn. Victor Lavrenko. PCA 1: curse of dimensionality. Inside Google: Page Rank. Demystifying Dimensionality Reduction. The Google Technology Stack. Posts PageRank and MapReduce Data mining and machine learning About Part of what makes Google such an amazing engine of innovation is their internal technology stack: a set of powerful proprietary technologies that makes it easy for Google developers to generate and process enormous quantities of data. According to a senior Microsoft developer who moved to Google, Googlers work and think at a higher level of abstraction than do developers at many other companies, including Microsoft: “Google uses Bayesian filtering the way Microsoft uses the if statement” (Credit: Joel Spolsky). This series of posts describes some of the technologies that make this high level of abstraction possible. The technologies I’ll describe include: The Google File System: a simple way of accessing enormous amounts of data spread across a large cluster of machines.
Together, these technologies make it easy to run large parallel jobs on very big data sets. Web Crawling PageRank I’ve never worked at Google. LIONlab - intelligent-optimization.org. GraphLab | GraphLab Create Gallery.
Reinforcement learning. Unsupervised learning. Supervised. PredictionIO Open Source Machine Learning Server. Books. Online courses.