Using AI in real-life scenarios
Here you will find different real-world AI applications developed by me, some of which are academic projects and others just for fun so there may be some errors in them. All are written in Spanish.
2025
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006. Computer vision in elevators
Will be published soon...
Go to the last published ->
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005. Biomedical segmentation with U-Net
This project implements a U-Net convolutional neural network to perform precise pixel-wise segmentation on biomedical images, covering everything from data preprocessing and augmentation through model training and evaluation. -> Python, Pytorch, U-Net, OpenCV, NumPy
12 min read
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004. BitaHealth
BitaHealth detects emotional states like stress or relaxation from ECG signals using HRV features and machine-learning models, and delivers results via a simple web API and React interface. -> React, PWA, Python, FastAPI, NeuroKit2, Pytorch
10 min read
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003. Early detection of kidney disease
Analysis and modeling of chronic kidney disease through data preprocessing in four versions and comparative training of multiple classification algorithms. -> Python, Pandas, Numpy, Scikit-learn (KNN, DecisionTree, RandomForest, GradientBoosting, LogisticRegression, SVM, MLP), Matplotlib, Seaborn, TensorFlow, Keras
8 min read
2024
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002. Transfer learning in convolutional models
Transfer learning with pre-trained models for face mask detection, from data preprocessing to fine-tuning and evaluation on different test sets. -> TensorFlow, Keras, Numpy, Pnadas, Matplotlib, OpenCV
7 min read
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001. AvIAry
Development of a multi-platform AI-based bird identification application. -> React, PyTorch, MongoDB, PWA, Express, Bootstrap
30 min read