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- Informatics Engineer (FICH-UNL) - Data Science & Machine Learning
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
DataWorkstation.jl
April 2, 2022 – August 15, 2022
A Julia framework to produce your data projects as a professional artist
View Projectmeli_datachallenge2019
December 14, 2020 – December 19, 2020
A Python solution for the MercadoLibre Data Challenge 2019
View ProjectDilemma.jl
July 27, 2020 – August 22, 2020
A Julia package to develop and evaluate context-free and contextual Multi-Armed Bandit policies
View Projectrl-iot-example
March 2, 2019 – December 22, 2022
Reinforcement Learning agent to solve Tic Tac Toe game, deployed on an IoT environment
View Projectacamica-ds-cor
February 14, 2019 – July 30, 2019
Repositorio con contenidos de la carrera de Data Science en Acámica (Córdoba)
View ProjectIMachineApp
March 14, 2018 – May 14, 2018
This Android application uses the CIEngine module to automatically manage the photos and images on the device. Then you will be able to manage the result according to your criteria, by moving or erasing images as you want.
View Projecttensorflow-mobilenet
September 28, 2017 – December 13, 2022
An example of usage of a MobileNet model in TensorFlow with Python
View Projectpyoselm
September 7, 2017 – Present
A Python implementation of Online Sequential Extreme Machine Learning (OS-ELM) for online machine learning
View ProjectCultural Fit Analysis
The candidate shows a strong inclination towards personal projects, indicating self-motivation and a passion for learning and applying new technologies. The diversity of projects, from deep learning to OCR and reinforcement learning, suggests an adaptable and curious mindset. However, the lack of team-based or professional experience makes it difficult to fully assess cultural fit in a collaborative work environment.
Soft Skills & Operational Fit
Insufficient data to assess soft skills or operational fit. The candidate's project descriptions are concise, but there is no information on collaboration, problem-solving approaches, or communication style.