- Reproduction of Existing Models: Goal: To accurately reproduce the results of the Half Life Regression and Logistic Regression models as presented in the paper ”A Trainable Spaced Repetition Model for Language Learning.” This involves implementing and validating these models on a relevant dataset to ensure that our foundational methodologies align with established research.
- Neural Network Implementation for Recall Probability: Goal: To extend the existing analysis by implementing advanced neural network models as an alternative to the traditional Logistic Regression approach for predicting the probability of recall in language learning. This includes designing, training, and evaluating neural network architectures to assess their effectiveness in this context.
- Find all the scripts in the src folder.
