GitHub - narenakash/Machine-Data-and-Learning: TLDR: Generic Algorithms, Decision Trees, Value Iteration, POMDPs, Bias-Variance. Data preprocessing using statistical techniques and visualization is crucial to understand and analyze the data before utilizing them to train a machine learning model. Several fundamental techniques for preprocessing are presented here.

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Name		Name	Last commit message	Last commit date
Latest commit History 36 Commits
Assignment 01: Bias-Variance Tradeoff		Assignment 01: Bias-Variance Tradeoff
Assignment 02B: Value Iteration in Reinforcement Learning		Assignment 02B: Value Iteration in Reinforcement Learning
Assignment 02C: Linear Programming and Markov Decision Process		Assignment 02C: Linear Programming and Markov Decision Process
Assignment 03: Genetic Algorithms		Assignment 03: Genetic Algorithms
Assignment 05: Partially Observable Markov Decision Processes		Assignment 05: Partially Observable Markov Decision Processes

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TLDR: Generic Algorithms, Decision Trees, Value Iteration, POMDPs, Bias-Variance. Data preprocessing using statistical techniques and visualization is crucial to understand and analyze the data before utilizing them to train a machine learning model. Several fundamental techniques for preprocessing are presented here.

machine-learning genetic-algorithm data-preprocessing markov-decision-processes pomdp value-iteration-algorithm bias-variance-tradeoff