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 RESUME  / SOME RELEVANT ASPECTS


 AREAS OF CONCENTRATION
  • Data Science.
  • Machine learning and Data Analysis.
  • Statistical data analysis with platforms R-project, R / BigData [medium-scale data], Python, Python / BigData [medium-scale data], SAS, Tableau (Desktop / Public).
  • Data Visualization and Graphics with platforms R-project, Python, SAS, Google, Tableau.
 AREAS OF INTEREST FOR RESEARCH
  • Data Science applications.
  • Machine learning applications.
  • Deep learning applications.
  • Statistical applications to social, health, education, marketing, business and engineering.
  • Classical multivariate methods applications. Application of prediction, regression, cluster, classification and scoring models.
 SOME LAST MADE PROJECTS
  • Python-MLearning: Digits recognition using Keras Library.
  • Python: Exploratory Data Analysis of the Digits recognition dataset (MNIST) using Python.
  • R-Project: Exploratory Data Analysis of the Digits recognition dataset (MNIST) using R.
  • Python-MLearning: Digits recognition using Extreme Gradient Boosting (XGBoost) and Sklearn Library.
  • Python-MLearning: Digits recognition using Logistic Regression and Sklearn Library.
  • R-MLearning: Digits recognition using Logistic Regression. SDP Consulting. Santiago, Chile.
  • Python-MLearning: Digits recognition using Random Forest Classifier (RF) and Sklearn Library.
  • Python-MLearning: Digits recognition using K-Nearest-Neighbors Classifier (Knn) and Sklearn Library.
  • Dynamic Pivot Tables with R, Python, and Online.
  • Python-MLearning: Digits recognition using PCA, Neural Network (NN) and Sklearn Library.
  • Python-MLearning: Digits recognition using Neural Network (NN) and Sklearn Library.
  • Python-MLearning: Classification using Gradient Boosting Machine (GBM) and Sklearn Library.
  • Python-MLearning: Classification using Extreme Gradient Boosting (XGBoost) and Sklearn Library.
  • Python-MLearning: Classification using Neural Network and Sklearn Library.
 SOME OF MY FACULTY EXPERIENCE
 Internacional:
  • Elgin Community College, Elgin, IL, USA.
  • Joliet Junior College, Joliet, IL, USA.
  • University of Saint Joseph, West Hartford, CT, USA.
  • University of Connecticut, Storrs, CT, USA.
 Chile:
  • Universidad Autónoma de Chile, Santiago-Temuco, Chile.
  • Universidad Santo Tomás, Valdivia-Santiago, Chile.
  • Universidad San Sebastían, Valdivia, Chile.
  • Universidad de La Serena, La Serena, Chile.
 EDUCATION
  • Data Science. Self taught (Autodidact).
    Different projects developed by me linked to areas of machine learning, data analytics, and Visualizations. I am always learning something new in this awesome field of development.
  • Master of Science in Statistics. Pontificia Universidad Católica de Chile, conferred September 2002.
    Thesis work: A multivariate logistic regression application to get a social-economics classification index.
  • Statistician. Universidad Austral de Chile, conferred July 1984.
    Thesis work: An implementation of a Statistics Quality Control Inspection Procedure using a mixed simple sampling method to be used in dairy products.
  • Bachelor of Science in Statistics. Universidad Austral de Chile, conferred July 1984.

 Hector Alvaro Rojas   /   Data Science, Visualizations and Applied Statistics.