IT Skills     Data and Databases     Data Management     Data Mining

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At the core of predictive analytics lie the models used to make predictions after the data has been collected and preprocessed. Explore predictive techniques, including A/B testing, Bayesian Networks, and the support vector machine (SVM).

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Objectives

A/B Testing start the course recognize what A/B testing is and where it is applicable establish an A/B test hypothesis and determine what to test implement A/B testing for web site optimization Naïve Bayes and Bayesian Belief Networks recognize key features of Naïve Bayes calculate the probability of an event occurring with Naïve Bayes identify various limitations of Naïve Bayes recognize features of Bayesian Belief Networks Support Vector Machines identify features of Support Vector Machines recognize how to transform linear non-separable data to linear separable data determine the optimal hyperplane Practice: Applying Predictive Approaches predict outcomes using A/B testing