Hi there, I'm Antonio Franco! 👋

About me

I am an aspiring computer scientist with a strong interest in AI and a long-term goal of pursuing an involvement in the field. I hold a Bachelor's degree in Computer Science from the University of Algarve and a Master's degree in Data Science and Computational Intelligence from Coventry University. I have 8 months of experience as a full-stack web developer, working on an IoT web software.

Some of my Skills:

• Programming Languages: Python, C#, Java, JavaScript, HTML, CSS, SQL, R, PHP

• Web Development: Full-stack development, IoT web software

• Data Science & AI: Data analysis, Machine Learning, Computational Intelligence

• Tools & Platforms: Git, GitHub, Jupyter Notebook, PyCharm, AndroidStudio, IntelliJ, Visual Studio, VS Code

Some of my Projects:

Bayesian_Network_Analysis_of_Metabolic_Syndrome

• Description: This project explores the use of different Bayesian Networks for analyzing Metabolic Syndrome. It investigates probabilistic relationships between various medical factors associated with the syndrome, utilizing Gaussian, Multinomial, and Hybrid Bayesian Networks. The project also implements different structure learning algorithms (Score-based, Constraint-based, and Hybrid) and evaluates models. The analysis suggests that the hybrid-based learning structure for a Gaussian Bayesian Network, when fitted with discretized data, provides the most accurate and interpretable model of the relationships between the factors contributing to metabolic syndrome achieving approximately 91% accuracy in predicting the ATPMetssynd diagnostic variable.

Emotion Recognition with Artificial Neural Networks

• Description: This project explores Geometric and Appearance approaches with Artificial Neural Network for Discrete Human Emotion Recognition from Static Face Images. It implements two primary approaches to extract features for recognizing human emotions from static facial images and aims to recognize discrete human emotions from static face images using Artificial Neural Networks. And found The combination of both approaches, leads to better performance, suggesting that both geometric and appearance features contain valuable information for emotion recognition.

Thesis Breast Cancer Diagnosis Screening via Deep learning

• Description: Investigated Meta Pseudo Labels for breast cancer CAD. The pipeline failed because the baseline segmentation model could not learn from the extremely limited labeled data. This research demonstrates that it's success is contingent on first establishing a functional supervised model, a step that was ultimately hampered by severe data scarcity, providing a critical analysis of the practical limits of advanced semi-supervised techniques.

• Description: This is my personal GitHub, serving as a central hub to showcase my projects, skills, and professional journey. But It is currently under development.

How to get in get in Touch:

• LinkedIn: in/antonio-mpembe-franco

• Email: antoniompembefranco@gmail.com

• GitHub Pages: tonyamf.github.io "Under development"

• Instagram: @teaamf