RESUME  / SOME RELEVANT ASPECTS

 AREAS OF CONCENTRATION
  • Data Science.
  • Machine learning, Statistical 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 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 PROJECTS
  • Machine Learning: Portugal Wine. Multiple Linear Regression to model Quality using R and K fold cross-validation. SDP Consulting. Santiago, Chile.
  • Machine Learning: Portugal Wine. Two Class approach for Red and White classification with Neural Network using R, NEURALNET Library and K fold cross-validation. SDP Consulting. Santiago, Chile.
  • Machine Learning: Portugal Wine. Two Class approach for Quality classification with Neural Network using R. SDP Consulting. Santiago, Chile.
  • Machine Learning: Portugal Wine. Two Class approach for Red and White classification with Neural Network using R. SDP Consulting. Santiago, Chile.
  • Machine Learning: Portugal Wine. Two Class approach for Red and White classification with Logistic Regression using R and K fold cross-validation. SDP Consulting. Santiago, Chile.
  • Machine Learning: Portugal Wine under Two Class approach for Quality classification with Logistic Regression using R and K fold cross-validation. SDP Consulting. Santiago, Chile.
  • Machine Learning: Portugal Wine under Two Class approach for red and white classification using R and K fold cross-validation. SDP Consulting. Santiago, Chile.
  • Machine Learning: A comparison of supervised learning algorithms applied to the classification problem in R with MLR Package and K fold cross validation. SDP Consulting. Santiago, Chile.
  • Machine Learning: A comparison of supervised learning algorithms applied to the classification problem in R with MLR Package. SDP Consulting. Santiago, Chile.
  • Machine Learning: A general way to run and compare most common supervised learning algorithms with R-project. SDP Consulting. Santiago, Chile.
  • Machine Learning: A comparison of supervised learning algorithms applied to the classification problem with Scikit-Learn Python library. SDP Consulting. Santiago, Chile.
  • Machine Learning: A comparison of supervised learning algorithms applied to the classification problem with caret R-project library. SDP Consulting. Santiago, Chile.
  • A More Realistic View of the Chilean Undergraduate Educational System Results. SDP Consulting. Santiago, Chile.
  • Data Analysis for the Chicagoland Motor Vehicle Theft Crime Incidents Jan/2001-Aug/2016. SDP Consulting. Santiago, Chile.
  • Mapping Chicagoland Motor Vehicle Theft Crime Incidents Jan/2001-August/2016. SDP Consulting. Santiago, Chile.
  • Cluster analysis application to the data results of the project "Evaluation of speed and reading comprehension in university students of first year of the health area of Universidad Mayor". Universidad Mayor / SDP Consulting. Santiago, Chile.
  • Comparison of Discriminant Analysis and Logistic Regression as predictive models for credit risks. SDP Consulting. Santiago, Chile.
  • Evaluation of speed and reading comprehension in university students of first year of the health area of Universidad Mayor. Universidad Mayor / SDP Consulting. Santiago, Chile.
  • Some tips over database management supported by R-project. SDP Consulting. Santiago, Chile.
  • Knowledge level, perceptions and information that students of Faculty of Medicine of Universidad Mayor have on violence against women in Chile. Universidad Mayor / SDP Consulting. Santiago, Chile.
 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 [fall 2017 fall/2011], Santiago-Temuco, Chile.
  • Universidad San Sebastían [2016 summer/2013], Valdivia, Chile.
  • Universidad de La Serena [2012], 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.