This course is taught by Dr.Heari. My main task includes:
- Creating and designing assignments
- Conducting classes for students in which extra contents and concepts were presented. Such as:
- A Probabilistic Cache Schedule Method
- Naive Bayes Classifier as a simple example of PGMs
- Why do we use MSE? Showing the connection between Maximum Likelihood Estimation with Gaussian noise and minimizing the MSE
- Bootstrap as a way to estimate a Statistic and then construct a confidence interval.
- Random Walk
Assignments have two parts.
- Calculating Probabilities
- Proofing the property
- Modeling some real world example with our statistical tools
Computer Experiment includes:
- Naive Bayes Classifier
- Sampling From a Distribution and Plotting corresponding Graphs
For more information about the question material checkout github