Optimal Marketing Strategy

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Related lectures (32)

Page 3 of 4

Exploration Bias

Explores regularization, learning algorithms, and subgaussian assumptions in machine learning.

Marketing & Sales Strategy: Fundamentals and Implementation

Explores marketing and sales fundamentals, lead generation, KPI tracking, and customer communication strategies for business growth.

Reactive Agents: Decision Processes

Explores reactive agents and decision processes, covering topics such as Markov Decision Processes and real-time agents.

Markov Chain Games

Explores Markov chain games, hitting probabilities, and expected hitting times in a target set.

Hidden Markov Models: Primer

Introduces Hidden Markov Models, explaining the basic problems and algorithms like Forward-Backward, Viterbi, and Baum-Welch, with a focus on Expectation-Maximization.

Linear Programming Techniques in Reinforcement Learning

Covers the linear programming approach to reinforcement learning, focusing on its applications and advantages in solving Markov decision processes.

Dynamic Programming: Optimal Decision Making

Explores dynamic programming for optimizing decision-making processes over time, using real-world examples like oil extraction and stock trading.

Birth & Death Chains: Analysis & Probabilities

Explores birth and death chains, hitting probabilities, and expected game durations in Markov chains.

Markov Chain: Configuration Sampling

Introduces the concept of a Markov process and chain in configuration sampling.

Sunny Rainy Source: Markov Model

Explores a first-order Markov model using a sunny-rainy source example, demonstrating how past events influence future outcomes.