Offered By: IBM
Classification of Yelp Reviews using Sentiment Analysis
Sentiment Analysis has become a very popular tool in extracting subjective information from the social media. It can help businesses to understand their brand, product or service better. In this Guided Project, you will be introduced to several Natural Language Processing Techniques to help you derive some meaning from yelp business reviews, as well as to build and test a classification model that can divide these reviews based on their polarities.
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765 EnrolledAt a Glance
Sentiment Analysis has become a very popular tool in extracting subjective information from the social media. It can help businesses to understand their brand, product or service better. In this Guided Project, you will be introduced to several Natural Language Processing Techniques to help you derive some meaning from yelp business reviews, as well as to build and test a classification model that can divide these reviews based on their polarities.
Learn by Doing
A Look at the Project Ahead
- Explore yelp business reviews dataset to perform text cleaning, vectorization, and classification
- Use scikit-learn library tools to extract some meaning from the sentiments
- Create a model to classify reviews based on their positive or negative sentiments
What You'll Need
- Basic Python knowledge
Instructor
Estimated Effort
1 Hour
Level
Intermediate
Skills You Will Learn
Data Science, Embeddable AI, Machine Learning, Python, Sentiment Analysis
Language
English
Course Code
GPXX0UN5EN