Sentiment analysis with VADER and TextBlob, and supervised text classification with scikit-learn

This post is the last of the three sequential posts on steps to build a sentiment classifier. Having done some exploratory text analysis and preprocessed the text, it’s time to classify reviews to sentiments. In this post, we will first look at 2 ways to get sentiments without building a model then build a custom model.

Before we dive in, let’s take a step back and look at the bigger picture really quickly. CRISP-DM methodology outlines the process flow for a successful data science project. In this post, we will do some of the tasks that a data scientist would go through during the **modelling **stage.

#classification #data-science #python #sentiment-analysis #machine-learning