Machine Learning Level Week 5 - Maria Mihaila

Technical Area

  • studied machine learning classification models (logistic regression, Naive Bayes , SVM) in more depth
  • Learned how to evaluate a classification model via performance metrics and confusion matrices
  • Grew familiar with hyperparameter tuning

Tools Used

  • sci-kit learn
  • pandas
  • Colab
  • git

Tasks Completed/Achievements

  • trained four machine learning classification models, and optimized the hyper parameters via Gridsearch.
  • Improved accuracy by 15-25% per model, the highest accuracy being 70% for logistic regression


  • Understand BERT (at least at theoretical level) by reading online articles
  • train BERT classifier on forum data