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Carlos Carrera

Carlos Carrera

Data Scientist jr.
Puebla, Puebla

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Sobre Carlos Carrera:

I am a fast learner, proactive, and enjoy working in a team environment. I am also passionate about data-driven decision-making and enjoy exploring complex data sets to extract insights and create value.

As a recent graduate with a diploma in Data Science, I am excited about the opportunity to apply my knowledge and skills to real-world projects and contribute to your team.

During my studies, I gained experience in data analysis, statistical modeling, and machine learning techniques. I have also worked on several projects that involved cleaning and preprocessing data, building predictive models, and visualizing results. In addition, I have experience working with programming languages such as Python, R, and SQL.

Experiencia

•Classification of places visualized on Voronoi Maps.
   Freelance Project 
    Description(s) of tasks/responsibilities
     Developed classification based on k-means clustering and naive Bayes classification for closed and most convenient places to go. 

      Developed Geographic Information Systems with weighted Voronoi diagrams for predicting the best choice of most convenient CdMx Health Centers.

Obtained a gain of 3% over the survivor probability for a pseudo-real-time database.


   •Researcher for classification and optimization.
   Undergraduate Research, Machine Learning and Computational Methods for Nuclear Science
      Researched regression algorithms(Logistic and Linear) for best Nuclear Fusion conditions.
      Developed algorithms for predicting the behavior of fusion experiments based on geometric characteristics.

Increasing a 10% the hypothetical efficiency results and publishing a paper in an international arbitrage journal: Physics of Plasmas .

• Researcher for car brand recognition.
  Undergraduate Research, Machine Learning Lab
   Researched using ANN and CNN for computational vision and an image similarity algorithm.
   The model developed obtained an accuracy of  75%  for image brand recognition based on characteristics of vehicles in photos of parking lots.

Educación

• B.S. in Physics at   UNAM(Universidad Nacional Autónoma de México)
    Relevant Coursework: Probability and Statistics, Applied Statistics, Computational Science and Applications, Machine Learning Algorithms, Logic, Numerical Methods for Science. 
   
  • Diploma in Data Science at  UNAM(Universidad Nacional Autónoma de México)
  Selected among 300 participants by showing skills in Machine Learning, Natural Language Processing, Computer Vision, and Model Forecasting and Optimization.
 

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