YoVDO

Language Classification with Naive Bayes in Python

Offered By: Coursera Project Network via Coursera

Tags

Machine Learning Courses Python Courses Data Preprocessing Courses Class Imbalances Courses

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

Related Courses

Introduction to Artificial Intelligence
Stanford University via Udacity
Natural Language Processing
Columbia University via Coursera
Probabilistic Graphical Models 1: Representation
Stanford University via Coursera
Computer Vision: The Fundamentals
University of California, Berkeley via Coursera
Learning from Data (Introductory Machine Learning course)
California Institute of Technology via Independent