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 eager to grow and learn. I firmly believe that learning is a continuous process, and I strive to expand my knowledge whenever possible.
🏍️ Besides data science, I love motorbiking. It allows me to unwind and enjoy the outdoors.
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Digital Twin for Quality Prediction in the 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. -
Fuel Consumption Reduction
I led a project aimed at reducing fuel consumption, which involved hardware development, modeling, and cloud integration. We achieved a 3% reduction in fuel consumption. -
Emotion Detection in Video
This project presents a practical application of computer vision to solve real-life problems. In the context of the 2020 coronavirus pandemic, virtual education became the primary method for continuing educational systems. However, there are challenges in implementing these technologies, such as the lack of proper tools to measure audience attention levels. We developed an algorithm to measure the level of attention of an audience based on the emotions expressed through their facial expressions.
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Interpreting Convolutional Neural Networks with LIME: Application in Cat and Dog Classification
In this report, we use the Local Interpretable Model-agnostic Explanations (LIME) method to explain the main features considered by a neural network. The goal is to understand how the model makes decisions when classifying images of cats and dogs.
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Superpixels and Histograms for Generating Feature Vectors
This document presents the methodology for implementing the superpixel method. It explains how superpixels can be used alongside histograms to generate feature vectors for image processing tasks.
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Bayesian Classifier
In this practice, we aim to perform feature extraction and class classification using the Bayesian method. The project involves applying Bayesian classification techniques to categorize data based on extracted features.
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If you have any questions or just want to chat, feel free to reach out to me:
- Email: [email protected]
- LinkedIn: Arturo (Arteck) Téllez