NLP 101 - Simple Classification
Image by Marco Oriolesi
Political Tweets - Simple Classifier: A Refresher in NLP
Welcome to this tutorial designed to give you a fresh update in Natural Language Processing (NLP)! In this project, we perform simple text classification to predict the political leaning of tweets. Our goal is to create a model that can accurately classify tweets as either Republican or Democratic using a Logistic Regression pipeline trained on preprocessed data.
What to Expect
- Installation and use of essential NLP libraries such as
tweet-preprocessor
,imbalanced-learn
, andgradio
. - Data manipulation and text preprocessing with Python modules like
pandas
,numpy
,spacy
, andscikit-learn
. - Creation and evaluation of a machine learning model using
LogisticRegression
andTfidfVectorizer
. - Handling imbalanced datasets using
RandomUnderSampler
fromimbalanced-learn
. - Model explanation with
eli5
and creation of a user-friendly interface withGradio
.
By the end of this tutorial, you will have a solid understanding of how to build a machine learning pipeline for text classification using Python libraries and how to create an interactive web application. Let’s dive in!
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