Gilberto G.

I am BS in Electrical Engineering graduated with honors. During my university career I specialized in the design and development of several tools for data processing, feature & pattern extraction, time-frequency analysis, signal convolution (see my portfolio), image classification, linear & nonlinear filtering of time sequences (1D), images (2D), hyper & multi spectral images (3D) as well as the implementation of genetic algorithms for the optimization of Objective Functions subject to linear and nonlinear constraints. In my degree project I implemented a land cover classifier for satellite images (hyper spectrals) using Sparse Signal Representation as an artificial intelligence method positioned in the state-of-the-art (see my portfolio). I currently have more than 3 years of experience in applications that enable extreme performance & accuracy improvements in Machine Learning and in the powerful field of Data Science. In particular, I have heavy expertise implementing models based on classical techniques such as: Binomial and Generalized Logistic Regression, Robust Regression, Neural Networks, Vector Support Machines, K-Nearest Neighbor as well as innovative techniques positioned in the state-of-the-art as Sparse Signal Representation, all of them in applications of Image classification, Denoising, Super Resolution, among others. I have heavy skills in Python and MATLAB (with experience in R as well) so I have used these powerful programming languages for the quickly, reliable and efficient development of my projects. I also carried out 3 masters courses in Biomedical Engineering of Mathematical Methods and Statistics applied to the Engineering, with which I have solid bases to analyze and infer well on the results obtained. Feel free to get in touch with me if you need to solve any problem related to: - Machine learning - Data science - Genetic Algorithms - Signal & Image Processing - Biomedical Image processing