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The aim is to find an optimal ML model (Decision Tree, Random Forest, Bagging or Boosting Classifiers with Hyper-parameter Tuning) to predict visa statuses for work visa applicants to US. This will help decrease the time spent processing applications (currently increasing at a rate of >9% annually) while formulating suitable profile of candidates more likely to have the visa certified.

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decision-tree-classifier bagging-ensemble random-forest-classifier gradient-boosting-classifier adaboostclassifier xgboost-classifier stacking-ensemble grid-search-hyperparameters grid-search-cross-validation accuracy-metrics

customer-profiling-using-ml-easyvisa's Introduction

Hi, this is Rochita! ๐Ÿ‘‹

  • Based out of Vancouver, British Columbia ๐Ÿ”๏ธ
  • Interested in Data Science, Machine Learning & Big Data ๐ŸŒฑ
  • Currently learning more on Deep Learning (NLP & CV) ๐Ÿ“š
  • Check out some of my projects ๐Ÿ”ญ

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