Sentiment analysis Machine Learning Projects - Download Project Source Code and Database
Sentiment analysis Machine Learning Projects aim to make a sentiment analysis model that will let us classify words based on the sentiments, like positive or negative, and their level. Before starting with our projects, let's learn about sentiment analysis.
Sentiment Analysis is a method to extract opinion which has diverse polarities. By polarity, it means positive, negative, or neutral. Sentiment analysis is also well-known as polarity detection and opinion mining. With its help, you can discover the nature of view reflected in social media feed, websites, and documents, etc.
Sentiment analysis Machine Learning Projects have become the hottest topics of the field due to its significance and the number of problems it solves and can answer. In our given tutorial, you will easily cover some not-so-simple projects. Specifically, you will be able to:
- Understand sentiment analysis from a practitioner's viewpoint
- Formulate the problem statement of sentiment analysis
- Inexperienced Bayes classification for sentiment analysis
- A simple case study in Python
- Determine how sentiment analysis affects several business grounds
Sentiment analysis is nothing but a study of opinions or emotions from text data. It identifies the opinion or sentiment of a person concerning a specific event. For sentiment analysis, users need to pass text or document that to analyze and generate a system or model that signifies a summarized form of the opinion of a given material.
Sentiment analysis Machine Learning Projects are useful for a movie review, product review, opinion about and customer services, etc. The project will help to decide if a specific item or service is good or bad/preferred or not preferred. It is also helpful to recognize people's opinions regarding any person or event and find the polarity of a text, whether neutral or positive/negative.