Language Classification with Naive Bayes in Python

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En este proyecto guiado, tú:

H​ow to clean and preprocess data for language classification

H​ow to train and assess a Multinomial Naive Bayes Model

H​ow to use subword units to counteract the effects of class imbalance in language classification

Clock60-75 minutes
IntermediateIntermedio
CloudNo se necesita descarga
VideoVideo de pantalla dividida
Comment DotsInglés (English)
LaptopSolo escritorio

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.

Habilidades que desarrollarás

StatisticsMachine LearningNatural Language Processing

Aprende paso a paso

En un video que se reproduce en una pantalla dividida con tu área de trabajo, tu instructor te guiará en cada paso:

  1. Exploratory data analysis of raw data, as well as some basic visualization

  2. Data cleaning and preprocessing relevant for task

  3. Theory behind and training of a Multinomial Naive Bayes Model

  4. M​aking adjustments to model to take into account class imbalance using theory behind Naive Bayes

  5. U​sing subword units to further counteract class imbalance and improve model performance

Cómo funcionan los proyectos guiados

Tu espacio de trabajo es un escritorio virtual directamente en tu navegador, no requiere descarga.

En un video de pantalla dividida, tu instructor te guía paso a paso

Instructor

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