Welcome to this workshop on artificial intelligence! In the following days, we will explore both basic and advanced techniques in machine learning, artificial neural networks, and deep neural networks. We will cover the theory behind these methods and provide hands-on practice using the Python programming language.
Dr. Wilfrido Gomez-Floresobtained a BS in Electronics and Communications Engineering from the Technological University of Mexico in 2004. He then earned an M.Sc. (2006) and D.Sc. (2009) in Electrical Engineering from Cinvestav. Since 2010, he has been a researcher at Cinvestav Tamaulipas Campus. Over the course of his career, he has produced over 100 publications, graduated 14 master's students and four doctoral students, and is a Level 2 in the SNII. His research interests include digital image analysis, pattern recognition, and machine learning.
Dr. Fernando Arce-Vegaholds a Bachelor's degree in Electronic Engineering and a Master's degree in Bioelectronics from Cinvestav. He completed his PhD in Computer Science at CIC-IPN and holds more than 24 certifications in machine learning and deep learning, as well as several scientific publications. As a Level 1 member of the National System of Researchers (SNII), he focuses on developing AI algorithms for optimizing biosensors and generating automatic mathematical models.
Introduction: Introduction to the Workshop
Day 1: Neural Networks
- Biological inspiration
- Gradient descent
- Single-layer neural networks
- Multi-layer perceptron
- SGD and optimizers
- Universal approximation theorem
Day 2: Deep Neural Networks
- What is deep learning?
- Convolutional neural networks
- LeNet-5 model
- Pre-trained CNN models
- Instance segmentation
- Convolutional autoencoder
- GRAD-CAM methods
- Lab
Dr. Wilfrido Gomez-Flores: [email protected]Dr. Fernando Arce-Vega: [email protected]
Zacatecas, November 2025:
