Readings are up for next week :) Following up on class discussion yesterday, here is the paper that I thought of assigning but was concerned about overloading people: https://www.microsoft.com/en-us/research/wp-content/uploads/2016/05/Bishop-MBML-2012.pdf This is not assigned, but it's an excellent paper and feedback is welcome. Also, someone asked about Gaussian processes yesterday. In thinking about the whole context of that discussion, I thought it might be helpful to recap some terminology. A random process is something that creates non-deterministic (uncertain) outcome Examples: Rolling dice (fair dice or not) Flipping a coin (fair coin or not) Random sampling Counterexamples Flipping a coin with two heads (because there is only 1 outcome, it is deterministic/certain) A random variable maps the outcome of a random process to a number. Example: Flipping a coin Random process: flipping a coin Random variable X where 1 is heads and 0 is tail...
Readings are up for next week 😀 Please also take a look at the data description for the latest Kaggle lab (link distributed yesterday). The lab for next week will step through the Zuur protocol to build a predictive model for this dataset.
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