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Name: Ana Caklovic
Type: User
Company: Utrecht University
Bio: Master's graduate in Applied Data Science
Name: Ana Caklovic
Type: User
Company: Utrecht University
Bio: Master's graduate in Applied Data Science
Used data from a 20 year span to model a time series that was used to forecast closing values of GSPC
Task was to build machine learning models that classify tweets about airlines into the categories “positive” or “negative”
Using regression analysis, we tested the significance of predictors (such as failures and travel time) to see if they influence the final grades of a student.
Used text analysis and natural language processing (NLP) to see if we could determine how credible a news source is.
Project to examine if state-of-the-art feature extractors (i.e., transformers like RoBERTa, MPNET, and SPECTER) can outperform classical feature extractors (i.e., tf-idf and Doc2Vec) when classifying systematic reviews as relevant or irrelevant (using the ASReview software)
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