I am a data science enthusiast with solid experience in modeling and project development. With a focus on machine learning and deep learning, I am always looking for new opportunities to apply my skills and learn more.

🔭 Currently, I am working as the Data Science Program Lead at Skills.Tech, where I am involved in program creation, teaching, student training, and coordinating the development of final projects.

🌱 I am always looking for opportunities to grow and learn. I firmly believe that learning is a continuous process and I try to expand my knowledge whenever possible.

🚴‍♂️ Besides data science, I love motorbiking. It allows me to unwind and enjoy the outdoors.

1. Digital Twin for Quality Prediction in Food Industry: I coordinated the development and implementation of a "Digital Twin" for predicting quality in the food industry. This project resulted in a 14% reduction in transformation costs.
2. Fuel Consumption Reduction: I led a project for reducing fuel consumption which required hardware development, modeling, and cloud connection. We achieved a 3% reduction in fuel consumption.
3. Deteccion de Sentimiento en video.: The following article has the goal to present a practical application of computer vision in a real life problem. In the context of 2020 coronavirus pandemic, virtual education takeoff as the main option to enable the scholar systems to continue. Though, there exists various problems in the implementation of this technologies. For instance, this technologies don ́t have any proper tool to measure the level of attention of an audience. Here, we present an algorithm to measure the level of attention of an audience based on the emotions expressed by their facial expressions. Link
4. Interpretacion del modelo de Redes Neuronales Convolucionales con LIME. Aplicacion en la clasificacion de perros y gatos: Este reporte busca, a traves del modelo: Explicación Agnostica al Modelo de la Interpretabilidad Local (LIME), explicar las principales caracter ́ısticas que toma en cuenta una red neuronal. Link
5. Superpixeles e histograma para generar Vectores de Características: En esta documento se presenta la metodología para la implementacion del método de superpixeles. Link
6. Clasificador Bayesiano: En esta practica se buscará realizar extracción de características y clasificacion de clases utilizando el m étodo de Bayes. Link

If you have any questions or just want to chat, feel free to get in touch with me.

• E-mail: [email protected]
• LinkedIn: Arturo (Arteck) Téllez