This repository contains projects and code developed as part of an Artificial Intelligence course. The course covered a variety of AI concepts and techniques, including neural networks, machine learning, and optimization algorithms. Below is a summary of the projects:
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Feed Forward Neural Network (FFNN):
- Implemented a Feed Forward Neural Network from scratch using NumPy.
- Employed the Keras library to classify the Arabic Handwritten Characters Dataset.
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Diabetes Detection:
- Utilized machine learning techniques such as K-Nearest Neighbors (KNN), Logistic Regression, and Decision Trees.
- Developed models to detect diabetes using healthcare data.
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Naive Bayes News Classifier:
- Developed a Naive Bayes Classifier from scratch for news classification tasks.
- Categorized news articles into different topics or classes.
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Minimax Algorithm for Sim Game:
- Implemented the Minimax Algorithm to create a game of Sim.
- Designed AI opponents for a simulation game using this decision-making algorithm.
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Genetic Algorithm for Equation Problems:
- Utilized a Genetic Algorithm to solve complex equation problems.
- Applied optimization techniques to mathematical tasks.
These projects provided hands-on experience in various AI domains, enhancing understanding and proficiency in artificial intelligence concepts and applications.
Feel free to explore the individual project folders for more details and code implementations.