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An extremely fast Python library to calculate the cognitive complexity of Python files, written in Rust.
This project demonstrates the use of generic bi-directional LSTM models for predicting importance of words in a spoken dialgoue for understanding its meaning. The model operates on human-annotated corpus of word importance for its training and evaluation. The corpus can be downloaded from: http://latlab.ist.rit.edu/lrec2018
In this research project, we aim to create an environment to gather structured data about machine learning experiments in order to analyze data and algorithmich dependencies.
Replication package of the paper titled "Generating Understandable Unit Tests through End-to-End Test Scenario Carving"
Replication package of the paper titled "Generating Understandable Unit Tests through End-to-End Test Scenario Carving"