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5-Finding a Reinforcement Learning Policy with a Markov Decision Process: Generalized Policy Iteration (GPI)
How to find a policy when you have a model of your Markov Decison Process (MDP)? There is a number of methods to do this that all fall under the umbrella of Generalized Policy Iteration (GPI). Here we will go through the two most notable methods – Policy Iteration and Value Iteration – and we…
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2-Bayes’ Theorem and its Applications to Classification and Sequence Models
Bayes’ Theorem and the Naïve Bayes classifier are foundational concepts in probability and machine learning. But what do they mean in practical terms? Let’s break it down with a simple example. Imagine you’re walking through the streets of Berlin and a stranger smiles and says “ciao!”. Naturally, you might wonder: Is this person Italian? Or…
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1-Intuition Behind the Birthday Paradox
The birthday problem refers to a family of statistical problems regarding the computation of various types the probability related to groups of people having the same birthday. For example, it could be about computing the chance of finding two people with the same date of birth in a group of fixed size. Or it could…