Applied Probability

Introduction to Graphical Models and Bayesian Networks

DSA ADS Course - 2022

Graphical Models, Bayesian Networks, Applied Probability, Probabilistic Causation, Causal Inference

Applied data scientists require high-level understanding of probability theory and specialized techniques to design systems and solve problems in the real world.  Graphical model formalism provides a natural framework for the design of new data science systems.

Evolutionary Game Theory: Game Theory, Applied Probability, Scenario Planning

DSA ADS Course - 2021

Game Theory, Applied Probability, Scenario Planning, Evolutionary Game Theory

Important to have basic knowledge of game theory. 

Game theory considers problems confronted by decision-makers with diverging interests like firms competing for a market. Players have to choose between strategies whose payoff depends on their rivals’ strategies. This interdependence leads to a mutual ‘outguessing’, as with chess (she thinks that I think that she thinks…).

The Sure Thing

DSA ADS Course - 2021

The Sure-Thing Principle, Causal Reasoning, Data-Driven Decision-Making, Algorithm Decision Making, Applied Probability, Nonlinear Utility Scale, Simpson’s Paradox, Blyth’s Game

Discuss applied probability, causal reasoning and types of decision making processes. Apply to both traditional algorithms and machine learning algorithms in decision making processes.

See also: The Sure-Thing Principle

The Sure Thing - 2021

Abstract

The Sure-Thing Principle

DSA ADS Course - 2021

The Sure-Thing Principle, Causal Reasoning, Data-Driven Decision-Making, Algorithm Decision Making, Applied Probability

Discuss applied probability, causal reasoning and types of decision making processes. Apply to both traditional algorithms and machine learning algorithms in decision making processes.

See also: The Sure Thing

The Sure-Thing Principle - 2016

Abstract

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