Software tools to collect Coronavirus sequences and create protein and nucleotide HMMs

This project aims to detect brain tumors using machine learning techniques. The code specifically trains and evaluates CNN models (VGG16, EfficientNetB0, MNASNet) on MRI images and compares their effectiveness.

a simple covid-19 reporting tool using laravel

This app tells us how to stop the spread of covid -19 it was very useful as covid hit last year

HC4, HC4m and HC5 covariance matrices

Back end de restaurante La Favorita, plataforma de pedidos online y gestión de producto del propio restaurante.

EasyCoV's service API.

As Tensorflow Kennard-Stone algorithmin uses euclidean distances, the need for an adaptation arrises when dealing with a big vector space that has unknown correlations between its variables, it may improve a lot neural networks performance.

As Tensorflow Kennard-Stone algorithmin uses euclidean distances, the need for an adaptation arrises when dealing with a big vector space that has unknown correlations between its variables, it may improve a lot neural networks performance.

This course covers modern computer vision, from image processing with OpenCV to deep learning with CNNs (ResNet, EfficientNet) and Transformers. Key topics include object detection (YOLO), image segmentation, and generative models (GANs, Stable Diffusion), with practical focus on transfer learning applications.