Information Theory (IT) as a basis for Machine Learning (ML)

سرفصل های دوره

Solve the game Mastermind using ML mathematical techniques. These include: IT, Simulated Annealing and Markov chains.

1. Introduction

1.1 Lecture1SolvingMastermindMLapproach.pdf

1.2 PromoPowerPoint.pdf

1. Outline of Course

2.1 Lecture2MachineLearningIntroduction.pdf

2. Introduction to Machine Learning Concepts

3.1 Lecture3ComparisonOfITbasedMLwithConventionalML.pdf

3. Comparing Information Theory and conventional Machine Learning methods.

4.1 entropy.zip

4.2 mmind ml.zip

4.3 mmindgame.zip

4. Setting up the Excel workbook

2. Machine Learning Applied to Mastermind

1. Mastermind example

2.1 Lecture6MLapproachToMastermind.pdf

2. Mastermind as an example of Machine Learning (Schematic explanation).

3.1 Lecture7MethodsUsed.pdf

3. Methods used to solve Mastermind using Machine Learning.

4.1 Lecture8MastermindExercises.pdf

4. Mastermind exercise

3. Automating Excel Solver

1.1 Lecture9SettingUpSolver.pdf

1. Setting up Excel Solver

2.1 Lecture10SomeSolverLimitations.pdf

2. Some Solver Limitations

3.1 Lecture11ApplyingNamedRangesToSolver.pdf

3. Applying Named Ranges to Solver

4.1 Lecture12AutomatingSolverUsingVBA.pdf

4. Automating Solver using VBA

4. Metropolis-Hastings applied to Mastermind

1.1 Lecture13MarkovChainMonteCarlo.pdf

1. Review of Metropolis-Hastings

2.1 Lecture14SimulatedAnnealing.pdf

2. Simulated Annealing

3.1 Lecture15ApplicationOfSimulatedAnnealing.pdf

3. Application of Simulated Annealing to Mastermind

4.1 Lecture16ComparativeScore.pdf

4. Comparative Score

5.1 Lecture17MHstrategy.pdf

5. Applying Metropolis-Hastings to Mastermind

5. Close

1.1 Lecture18Conclusions.pdf

1. Conclusions

6. Other applications

1.1 Lecture19OtherGameApplications.pdf

1. Applications to other games.

2.1 Lecture20ScienceEngineering.pdf

2. Application to other science and engineering problems.

3.1 Lecture21Bonus.pdf

3. Bonus

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تولید کننده: Udemy