NTUA AI Coursework

Student: Michael-Athanasios Peppas (03121026) Institution: National Technical University of Athens, ECE

This repository includes Google Colab notebooks from three core courses: Artificial Intelligence, Machine Learning, and Neural Networks & Deep Learning. Each course contains two comprehensive lab projects with supporting code and data.

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Courses

Artificial Intelligence

• AI_Lab1: Maze generation, search algorithms (BFS, Dijkstra, A*, Greedy), and adversarial planning with Alpha-Beta agents.
• AI_Lab2: Hybrid movie recommender combining SWI-Prolog symbolic reasoning and Python for data handling and evaluation.

See Artificial_Intelligence/README.md for detailed instructions, key concepts, and results.

Machine Learning

• ML_Lab1: RainTomorrow classification: data preprocessing, feature engineering, model training with scikit-learn, and evaluation.
• ML_Lab2: Salinas hyperspectral clustering and classification using KMeans, Fuzzy C-Means, PCA, and CNN feature extraction.

See Machine_Learning/README.md for detailed instructions, key concepts, and results.

Neural Networks & Deep Learning

• DL_Lab1: WideResNet architectures on CIFAR-10, Mixup augmentation, calibration measurement, and robustness on CIFAR-10-C.
• DL_Lab2: Transformer fine-tuning for sentiment, PiQA, TruthfulQA, and Winogrande tasks using Hugging Face.

See Neural_Networks_and_Deep_Learning/README.md for detailed instructions, key concepts, and results.

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Repository Structure

ntua-ai-coursework/
├── Artificial_Intelligence/
│   ├── AI_Lab1/
│   ├── AI_Lab2/
│   └── README.md
├── Machine_Learning/
│   ├── ML_Lab1/
│   ├── ML_Lab2/
│   └── README.md
├── Neural_Networks_and_Deep_Learning/
│   ├── DL_Lab1/
│   ├── DL_Lab2/
│   └── README.md
├── LICENSE
└── README.md

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Prerequisites

• Python 3.8+

• Libraries:

  pip install numpy pandas matplotlib scikit-learn torch torchvision torchaudio transformers datasets evaluate sentence-transformers tqdm

• SWI-Prolog (v8.x): required for AI_Lab2

  sudo apt-get install swi-prolog
  pip install pyswip

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Getting Started

1. Clone the repository

   git clone <repo_url> ntua-ai-coursework
   cd ntua-ai-coursework

2. Install dependencies as listed above.

3. Explore each course by opening its README.md and running the lab notebooks in Google Colab or Jupyter.

4. For DL labs, download and extract the CIFAR-10-C dataset into the specified utils/data folders.

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License

This project is licensed under the MIT License. See LICENSE for details.

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Prepared by Michael-Athanasios Peppas (03121026)