I am a Lead Data Scientist with over 8 years of experience in machine learning, reinforcement learning, data engineering, and AI applications. My work spans various industries, including banking, energy, and government research projects. I specialize in algorithm optimization, large-scale data analysis, and AI-driven decision-making.
I also enjoy gaming! You can find me on Fortnite under the username dataperromx 🕹️.
I am passionate about sharing knowledge and mentoring others in the fields of data science, machine learning, and AI. Below are some of the key talks and workshops I have led:
| Event | Topic | Location | Year | Links |
|---|---|---|---|---|
| SG Data Day 2022 | Archivos de la Represión & AI for Social Good | Mexico City, Mexico | 2022 | Talk Details |
| RIIA Hackathon | Machine Learning for Historical Archives | Virtual | 2021 | YouTube |
| Introduction to Data Science with Spark | Hands-on Workshop on Apache Spark | Mexico City, Mexico | 2018 | GitHub Repo |
| RIIA Workshop | AI Applications in Historical Analysis | Mexico City, Mexico | 2022 |
I am passionate about using AI for social good. One of my key projects involves applying machine learning to analyze historical security files, helping uncover hidden patterns in national archives.
| Project Name | Description | Technologies | Year | Repository |
|---|---|---|---|---|
| DFS OCR Reader | Applied machine learning & OCR to analyze and extract text from national security archives. | Yolov5, Pytorch, MachineLearning, Python, OpenCV, Tesseract OCR, RegEx | 2022 | GitHub Repo |
Data is at the core of my work. Here are some projects focused on data pipelines, big data, and analytics.
| Project Name | Description | Technologies | Year | Repository |
|---|---|---|---|---|
| LinkedIn Web Scraping | Automated data extraction from LinkedIn using Selenium to gather job listings and profile insights. | Python, Selenium, Web Scraping | 2017 | GitHub Repo |
Building intelligent systems is a core part of my work.
| Project Name | Description | Technologies | Year | Repository |
|---|---|---|---|---|
| MSC_AI_KW_Project | A team-based project that leverages metaheuristic algorithms and semantic data integration (YAGO & Wikidata) to optimize personalized music recommendations. | Python, SPARQL, Flask, JavaScript, Metaheuristic Algorithms | 2025 | GitHub Repo |
I have worked on metaheuristic algorithms to solve complex optimization problems.
| Project Name | Description | Technologies | Year | Repository |
|---|---|---|---|---|
| MSC_AI_Assigment | Evolutionary Algorithm for the Travelling Salesman Problem (TSP) using GA and B&B. | Python, Genetic Algorithms, Branch and Bound, Jupyter Notebooks, LaTeX | 2024 | GitHub Repo |
I explore autonomous decision-making models and large language models.
| Project Name | Description | Technologies | Year | Repository |
|---|---|---|---|---|
| reinforcement_learning_examples | A demonstration of a Deep Q-Network (DQN) implementation using Keras for reinforcement learning. It features a custom training loop with target network updates, reward computation, and grid-based environment simulations for autonomous decision-making. | Python, TensorFlow, Keras, NumPy, scikit-learn, matplotlib | 2018 | GitHub Repo |
🔹 Programming Languages: Python, Scala, SQL, R
🔹 Scripting & Markup: LaTeX, Markdown
🔹 Deep Learning & AI: TensorFlow, Keras, PyTorch, YOLOv5, Tesseract, Scikit-learn, XGBoost
🔹 Metaheuristic Algorithms: Genetic Algorithms, Branch and Bound
🔹 Data Engineering & Big Data: PySpark, GraphX, Kafka, AWS Glue, Redis, Timestream
🔹 Data Analysis & Notebooks: Jupyter Notebooks, Pandas
🔹 Visualization: Google Data Studio, Amazon QuickSight, Qlik
🔹 DevOps & Cloud: AWS, Docker, Git
Interested in collaborating? Feel free to:
- ⭐ Star the repository
- 🛠️ Open a pull request with improvements
- 🗣️ Reach out via LinkedIn
📌 LinkedIn: juancarlosgonzalezaguilar
📌 GitHub: perrosdatos
📌 Email: carlosgonzagular@email.com
📌 Discord: @dataperromx
I’m always open to new ideas and collaborations! Feel free to explore my repositories, and if you find something interesting, let’s connect!