deepLearningExamBSC

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Deep Learning Exam Project

This repository contains my solutions for a university exam on Deep Learning.
The notebook demonstrates text preprocessing, feature extraction, and the implementation of neural networks with Keras for classification tasks.

📂 Contents

• 501019_exam_session_june.ipynb — the main notebook with all exercises and solutions
• requirements.txt — Python dependencies for running the notebook
• README.md — project description

🚀 What I Did

• Data loading and preprocessing
• Text feature extraction with CountVectorizer and TF-IDF
• Data scaling and encoding with scikit-learn
• Neural network modeling with Keras (Dense layers, Dropout, Regularization)
• Model training, evaluation, and F1-score reporting
• Exploration of different preprocessing strategies and model performance

📚 Libraries Used

The following main libraries were used in this project:

• numpy — numerical operations
• pandas — data manipulation
• scikit-learn — preprocessing, vectorization, train/test split, F1-score evaluation
• keras / tensorflow — neural network modeling and training
• re — regex-based text cleaning

🔧 Installation

Clone this repository and set up the environment:

git clone https://github.com/IvanAlKhayat/deep-learning-exam.git
cd deep-learning-exam
pip install -r requirements.txt