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Daniel Augusto Muñoz Viveros

Exploring Data and Discovering Patterns!

My experience combines data analysis, predictive modeling, and AI-based tool development with a hands-on approach to projects that integrate technology and innovation. I aspire to build intelligent, understandable, and scalable solutions that contribute.

👨‍💻 About Me


Hi! I'm Daniel — Data Scientist, Master in Information Processing Sciences, and an insatiable explorer of the world.


I specialize in applying artificial intelligence and data science to solve real-world problems in health, science, and society. With a strong background in statistics, machine learning, and programming, I have developed predictive models using tools like Python, R, SQL, Pandas, Scikit-Learn, TensorFlow, Docker, and AWS — always focused on improving decision-making and creating meaningful impact.



I enjoy developing applications and tools based on artificial intelligence and machine learning, transforming predictive models into interactive and accessible solutions for users.


When I'm not coding or analyzing data, I love football ⚽, reading biographies of brilliant minds 💡, and relaxing with great music 🎧.


👉 Interested in collaborating, sharing ideas, or just chatting about AI or data science?


📩 Let's Talk 📄 Download my CV
Daniel's Photo

🛠️ Technical Skills


Python
Python
R
R
NumPy
NumPy
Pandas
Pandas
SciPy
SciPy
Matplotlib
Matplotlib
Scikit-learn
TensorFlow
TensorFlow
VS Code
VS Code
MySQL
MySQL
PostgreSQL
PostgreSQL
Power BI
Power BI
Git
Git
GitHub
GitHub
AWS
Docker
Docker

🚀 Projects


⚽ Predictor Mundial 2026
Score prediction application developed with Python and Streamlit, powered by machine learning models and historical statistics of international football.
🔗 View app 🔗 View repository
🏆 Quiniela Mundial 2026
Interactive platform for competing with friends during the 2026 World Cup, allowing users to submit predictions and accumulate points based on prediction accuracy.
🔗 View app 🔗 View repository
📊 COVID-19 in Mexico Chart
Interactive visualization of confirmed cases, deaths, and recoveries by state. Tools: Python, PostgreSql, PowerBi.
🔗 View repository
🧬 Influential Factors on Post-COVID Antibodies
Retrospective study using AI techniques to identify clinical and sociodemographic variables that influence COVID-19 antibody levels. Title: "Identification of factors of antibody levels in post COVID-19 individuals: public health approach."
🔗 View publication
😷 Mask Detection
Computer vision system that identifies if a person is correctly wearing a mask using convolutional neural networks. Tools: Python, TensorFlow, AWS, Docker.
🔗 View repository
😴 Sleep Stress Detection
Sleep stress prediction using machine learning models to detect stress and sleep disorders. Tools: Python, Docker.
🔗 View repository
🩺 Cirrhosis Prediction
Cirrhosis prediction model using clinical patient data with supervised classification algorithms. Tools: Python, Scikit-learn, AWS, Docker.
🔗 View repository

📬 Contact


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