Emotion & Sentiment Analysis with/without NLTK using Python
Analyze Emotions ( happy, jealousy, etc ) using NLP Python & Text Mining. Includes twitter sentiment analysis with NLTK
Description
Welcome to this course on Sentiment and Emotion/Mood analysis using Python
Have you ever thought about how Politicians use Sentiment Analysis? They use to find which topics to talk about in public. A topic can have different sentiments (positive or negative) and varying emotions associated with it. Politicians analyze tweets/internet content to find out these topics and use them to find holes in the opposition.
How Google Maps classifies millions of locations like Restaurants by analyzing the Reviews
How Amazon shows products which evoke Positive Sentiments/Emotions for the buyers
How KFC use it to do Market Research and Competitor Analysis
If you want to know Technology running behind, this is the Sentiment Analysis/Mood Analysis course which is going to use Natural Language Processing ( NLP ) and Text Mining to analyze different moods in a text ( example - Sadness, Excitement, Loneliness etc)
What You Will Learn!
- Find out Emotions in a text ( happiness, sadness, jealousy etc. )
- Positive and Negative - Sentiment Analysis
- Scrap Tweets from Twitter and find out the emotion and sentiment of those tweets
- Learn Natural Language Processing Techniques
- Cleaning Text and Data for Language Processing ( NLP )
- Learn to create graphs using Matplotlib and plot the emotions graph
- Learn NLTK for Sentiment Analysis and Natural Language Processing
Who Should Attend!
- Developers wanting to analyze text and extract meaning & information from it.
- Beginner Python Developers who are curious about Natural Language Processing ( NLP )
- Anyone interested in learning about Sentiment and Emotion/Mood Analysis