Language Classification with Naive Bayes in Python
Offered By: Coursera Project Network via Coursera
Course Description
Overview
In this 1-hour long project, you will learn how to clean and preprocess data for language classification. You will learn some theory behind Naive Bayes Modeling, and the impact that class imbalance of training data has on classification performance. You will learn how to use subword units to further mitigate the negative effects of class imbalance, and build an even better model.
Syllabus
- Language Classification with Naive Bayes in Python
- In this 1-hour long project, you will learn how to design a model end-to-end that can classify sentences into one of Slovak, Czech, and English. During this process, you will implement relevant preprocessing steps, as well as address class imbalance in your training set by employing the learned theory of Naive Bayes Models, as well as implementing a more advanced technique: subword units.
Taught by
Ari Anastassiou
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