Project: Language Classification with Naive Bayes in Python

Offert par
Rhyme
Dans ce projet guidé, vous :

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
IntermediateIntermédiaire
CloudAucun téléchargement requis
VideoVidéo en écran partagé
Comment DotsAnglais
LaptopDesktop only

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.

Les compétences que vous développerez

StatisticsMachine LearningNatural Language Processing

Apprendrez étape par étape

Votre enseignant(e) vous guidera étape par étape, grâce à une vidéo en écran partagé sur votre espace de travail :

  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

Comment fonctionnent les projets guidés

Votre espace de travail est un bureau virtuel situé dans votre navigateur, aucun téléchargement n'est requis

Votre enseignant(e) vous guide étape par étape dans une vidéo en écran partagé

Foire Aux Questions

Foire Aux Questions

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