- Computer Vision: Leveraging image processing and deep learning to enable machines to interpret and understand visual data.
- AWS: Utilizing Amazon Web Services for scalable and robust cloud computing solutions.
- Azure: Employing Microsoft Azure for computer vision, chatbots, machine learning models, document intelligence, etc.
- Tensorflow: Implementing machine learning models using this powerful open-source library.
- Pytorch: Building and training neural networks with this flexible and efficient deep learning framework.
- Robotics: Developing intelligent robotic systems for the automotive and food industries.
- Geospatial Data: Analyzing and visualizing geographical data to uncover spatial patterns and insights.
- RAG (Retrieval-Augmented Generation): Enhancing generative models with external knowledge retrieval for more accurate and relevant outputs.
- LLMs (Large Language Models): Working with advanced language models for natural language understanding and generation.
- Web Scraping: Extracting valuable data from websites for analysis and insights.
- Agile Methodologies: Applying agile principles for efficient project management and development.
- Prompt Engineering: Crafting effective prompts to improve the performance of AI models.
 
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Participation in the development of a Generative Artificial Intelligence platform to generate creative and customized content for Nike & Adidas products. Participation in the development of chatbots, using Langchain, ChromaDB, Postgres, vector databases, and RAG techniques. Development of an ML algorithm to determine pedestrian traffic in Spain.
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