Easy Naive Bayes Classifier Tutorial with Python and sklearn - Sentiment Analysis Example
My name is Rohit.
Learn how to implement a Naive Bayes classifier in Python using the popular sklearn library. In this tutorial, we'll walk through a simple example of sentiment analysis, where we classify sentences as neutral, positive, or negative based on the frequency of their words. We'll cover the entire process from data preparation to model training and evaluation, and provide step-by-step instructions and explanations along the way. Whether you're new to machine learning or just looking to expand your skills, this tutorial is a great starting point.
𝐁𝐨𝐨𝐤 ( 𝐅𝐫𝐨𝐦 𝐂𝐨𝐝𝐞 𝐓𝐨 𝐂𝐨𝐧𝐧𝐞𝐜𝐭𝐢𝐨𝐧𝐬: 𝐀 𝐃𝐞𝐯𝐞𝐥𝐨𝐩𝐞𝐫’𝐬 𝐠𝐮𝐢𝐝𝐞 𝐭𝐨 𝐛𝐮𝐢𝐥𝐝𝐢𝐧𝐠 𝐚 𝐬𝐨𝐜𝐢𝐚𝐥 𝐜𝐚𝐫𝐞𝐞𝐫 )
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Keywords: Naive Bayes, Python, sklearn, Sentiment Analysis, Tutorial, Machine Learning, Data Science, Natural Language Processing, CountVectorizer, MultinomialNB, Classification
Tags: #ai #python #code #machinelearning #coding #programming #sklearn #tutorial #datascience #naturallanguageprocessing
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