Concentration InequalitiesCovers concentration inequalities and sampling methods for estimating unknown distributions, with a focus on population infection rates.
Diffusion ModelsExplores diffusion models, focusing on generating samples from a distribution and the importance of denoising in the process.
Review Session: Module 1Introduces inferential statistics, covering sampling, central tendency, dispersion, histograms, z-scores, and the normal distribution.
Deep Learning Modus OperandiExplores the benefits of deeper networks in deep learning and the importance of over-parameterization and generalization.
Parameter EstimationDiscusses parameter estimation, including checks, quality, distribution, and statistical properties of estimates.
Distribution EstimationCovers the estimation of distributions using various methods such as minimum loss and expectation.
Property TestingCovers the concept of property testing using statistical methods.
Pizza Making ProcessCovers the process of making pizza, sampling, averages, dispersion, residuals, and normal distribution.
