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martinp95/README.md
github linkedin kaggle

Hey 👋, I'm Martín Peláez

Software Engineer with an MSc in Artificial Intelligence. I build practical, end-to-end projects across backend, data and applied ML — from Java/Python applications to on-prem containerized setups with Docker and ML prototypes that are designed to be reproducible and easy to run.

What you’ll find in this profile

You’ll see a mix of production-minded engineering projects (clean code, clear README, pragmatic decisions), on-prem learning labs (Dockerized services and environments), and applied AI work (especially computer vision and classification problems) whenever it makes sense to solve a real need.

Languages and Tools

Java Spring Python PostgreSQL Docker BigQuery PyTorch TensorFlow OpenCV

Featured work

If you want the quickest overview, start with the pinned repositories below. I try to keep each project straightforward: how to run it, what problem it solves, and what I learned building it.

Pinned Loading

  1. meeting-transcriber meeting-transcriber Public

    AI-powered meeting transcription tool that converts audio and video files into accurate text using Google Gemini. Includes speaker diarization, timestamps, DOCX export, history, dark mode, and mult…

    TypeScript

  2. heart_disease_classification heart_disease_classification Public

    Example project for data analysis and modeling focused on heart disease detection

    Jupyter Notebook

  3. flask_api_chinook flask_api_chinook Public

    A production-ready RESTful API built with Flask, SQLAlchemy, and Marshmallow, based on the classic Chinook database. It exposes endpoints to browse artists, albums with support for pagination, nest…

    Python

  4. Plant-Disease-Classifier-RESTService Plant-Disease-Classifier-RESTService Public

    This repository contains a plant disease classification project using images, developed as a REST service. The application is built using Flask and TensorFlow, and is configured to be deployed in a…

    Python

  5. Computer-Vision-Experimentation-Framework Computer-Vision-Experimentation-Framework Public

    This project provides a framework for running machine learning experiments involving image classification. It includes components for data loading, preprocessing, model training, and result reporting.

    Python

  6. Plant-Pathogen-Multiclass-Classifier Plant-Pathogen-Multiclass-Classifier Public

    This notebook demonstrates how to implement a multiclass classifier for plant pathogens in Keras and how it was used with Plant Pathogen Dataset on Kaggle

    Jupyter Notebook