Language Classification with Naive Bayes in Python

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In this Guided Project, you will:

How to clean and preprocess data for language classification

How to train and assess a Multinomial Naive Bayes Model

How to use subword units to counteract the effects of class imbalance in language classification

60-75 minutes
Intermediate
No download needed
Split-screen video
English
Desktop 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.

Skills you will develop

  • Statistics

  • Machine Learning

  • Natural Language Processing

Learn step-by-step

In a video that plays in a split-screen with your work area, your instructor will walk you through these steps:

  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. Making adjustments to model to take into account class imbalance using theory behind Naive Bayes

  5. Using subword units to further counteract class imbalance and improve model performance

How Guided Projects work

Your workspace is a cloud desktop right in your browser, no download required

In a split-screen video, your instructor guides you step-by-step

Instructor

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At the top of the page, you can press on the experience level for this Guided Project to view any knowledge prerequisites. For every level of Guided Project, your instructor will walk you through step-by-step.

Yes, everything you need to complete your Guided Project will be available in a cloud desktop that is available in your browser.

You'll learn by doing through completing tasks in a split-screen environment directly in your browser. On the left side of the screen, you'll complete the task in your workspace. On the right side of the screen, you'll watch an instructor walk you through the project, step-by-step.