List of Figures

Chapter 1. Building applications for the intelligent web

Figure 1.1. Overview of an intelligent algorithm. Such algorithms display intelligence because the decisions they make change depending on the data they’ve received.

Figure 1.2. Graphical overview of one aspect of the Google Now project. In order for Google Now to make predictions about your future locations, it uses a model about past locations, along with your current position. Priors are a way to distill initially known information into the system.

Figure 1.3. The intelligent-algorithm lifecycle

Figure 1.4. Taxonomy of intelligent algorithms

Figure 1.5. The machine-learning data flow. Data is used to train a model, which can then be applied to previously unseen data. In this case, the diagram illustrates classification, but the diagrams for clustering and regression are conceptually similar.

Figure 1.6. ROC curves for two theoretical classifiers. As we modify the algorithm parameter, we see a change in behavior against a given dataset. The closer the trace gets to touching the top-left corner of the diagram, the closer that classifier is to being ideal, because the TPR=1 and the TNR=1 (because TNR=1 – FPR).

Chapter 2. Extracting structure from data: clustering and transforming your data