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CS230 Deep Learningcs230.stanford.edu/projects_fall_2018/reports/12447287.pdf · Similarity and tf-idf are insufficient for questions but are more effective for bags of words approaches

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Page 1: CS230 Deep Learningcs230.stanford.edu/projects_fall_2018/reports/12447287.pdf · Similarity and tf-idf are insufficient for questions but are more effective for bags of words approaches
Page 2: CS230 Deep Learningcs230.stanford.edu/projects_fall_2018/reports/12447287.pdf · Similarity and tf-idf are insufficient for questions but are more effective for bags of words approaches
Page 3: CS230 Deep Learningcs230.stanford.edu/projects_fall_2018/reports/12447287.pdf · Similarity and tf-idf are insufficient for questions but are more effective for bags of words approaches
Page 4: CS230 Deep Learningcs230.stanford.edu/projects_fall_2018/reports/12447287.pdf · Similarity and tf-idf are insufficient for questions but are more effective for bags of words approaches
Page 5: CS230 Deep Learningcs230.stanford.edu/projects_fall_2018/reports/12447287.pdf · Similarity and tf-idf are insufficient for questions but are more effective for bags of words approaches
Page 6: CS230 Deep Learningcs230.stanford.edu/projects_fall_2018/reports/12447287.pdf · Similarity and tf-idf are insufficient for questions but are more effective for bags of words approaches

cs230.stanford.educs230.stanford.edu/projects_fall_2018/reports/12449174.pdf · YOLO ensembles performs marginally better than YOLO as a single model. In addition, some steps ofChexNet

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