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baysian-network

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Practical experience in hyperparameter tuning techniques using the Keras Tuner library. Hyperparameter tuning plays a crucial role in optimizing machine learning models, and this project offers hands-on learning opportunities. Exploring different hyperparameter tuning methods, including random search, grid search, and Bayesian optimization

  • Updated Dec 5, 2023
  • Jupyter Notebook

This repository contains a collection of lab exercises and exams from the TDDE15: Advanced Machine Learning course taking at Linköping Univerity during the fall 2024. The main topics are: Bayesian Networks, Hidden Markov Models, Q-learning, REINFORCE, and Gaussian Processes.

  • Updated Nov 6, 2024
  • R

A collection of AI algorithms and techniques covering intelligent agents, search strategies (BFS, DFS, A*), probabilistic reasoning (Bayesian networks, HMM), neural networks (feed-forward, Hopfield), and reinforcement learning. Topics include adversarial search, alpha-beta pruning, decision trees, Markov processes, and game theory applications.

  • Updated Oct 23, 2024
  • Python

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