Personalized Medicine: Ezekiel

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Related lectures (13)

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Bayesian Inference: Optimal Estimation

Explores optimal Bayesian inference, denoising, scalar estimation, and phase transitions.

Monte Carlo: Markov Chains

Covers unsupervised learning, dimensionality reduction, SVD, low-rank estimation, PCA, and Monte Carlo Markov Chains.

Bayesian Extremes: Markov Chain Monte Carlo

Explores Bayesian techniques for extreme value problems, including Markov Chain Monte Carlo and Bayesian inference, emphasizing the importance of prior information and the use of graphs.

Linear Regression: Regularization Overview

Explores linear regression fundamentals, emphasizing the importance of regularization techniques to enhance model performance.

Inference Problems & Spin Glass Game

Covers inference problems related to the Spin Glass Game and the challenges of making mistakes with preb P.

Spam Filtering: Bayesian Approach

Covers the Bayesian approach to spam filtering and calculating probabilities for identifying spam messages.

Bayesian Parameter Estimation

Covers an example of Bayesian parameter estimation and the trade-off between bias and variance in supervised learning.

Bayesian Inference: Optimal Decisions

Explores Bayesian inference for optimal decision-making in hypothesis testing scenarios.

Bayesian Inference: Precision in Gaussian Model

Explores Bayesian inference for precision in the Gaussian model with known mean, using a Gamma prior and discussing subjective vs objective priors.

Modeling Biomolecular Simulations and Experiments

Explores the evolution of biomolecular simulations, emphasizing accurate models, increased sampling, and the transformative role of simulations in predicting experimental outcomes.