Sampling Methods

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Successfully Evaluating Predictive Modelling (edX)

Gain an in-depth understanding of evaluation and sampling approaches for effective predictive modelling using Python. A predictive exercise is not finished when a model is built. This course will equip you with essential skills for understanding performance evaluation metrics, using Python, to determine whether a model is performing [...]
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Probabilistic Graphical Models 2: Inference (Coursera)

Probabilistic graphical models (PGMs) are a rich framework for encoding probability distributions over complex domains: joint (multivariate) distributions over large numbers of random variables that interact with each other. These representations sit at the intersection of statistics and computer science, relying on concepts from probability theory, graph algorithms, machine [...]
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Introduction to Probability and Data with R (Coursera)

This course introduces you to sampling and exploring data, as well as basic probability theory and Bayes' rule. You will examine various types of sampling methods, and discuss how such methods can impact the scope of inference. A variety of exploratory data analysis techniques will be covered, including numeric [...]
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