This repository contains projects developed as part of the course PSI3471 – Fundamentals of Intelligent Electronic Systems (Fundamentos de Sistemas Eletrônicos Inteligentes), an introduction to Machine Learning and Computer Vision.
All algorithms, implementations, and analyses were created during the course, either as exercises, project deliverables, or personal extensions of class topics.
- Basic Image Processing
- Feature Extraction (e.g., edges, corners)
- Classical Machine Learning Algorithms (SVM, KNN, Decision Trees, Naive Baynes)
- Basic Neural Networks and Deep Learning Foundations
- Object Detection and Recognition
- Evaluation Metrics and Model Performance Analysis
- Python, C++
- NumPy, OpenCV2, scikit-learn, TensorFlow Keras, Matplotlib, Seaborn
- Jupyter Notebooks (for prototyping and visualization)
All code and solutions were developed for educational purposes as part of coursework. The repository serves both as a record of the learning process and as reference material for future projects.