This repository looks at Tweets and classifies them as positive, negative, or neutral
The entire program is written in Python (libraries used: scikit-learn, pandas, numpy)
Some concepts Used:
- TFIDF Vectorizer: Vectorize the tweet into an array of numerical values making it easier to test
- KFold: Uses Cross Validation to evaluate the performance of my model by splitting the result in K subsets
- SVC: Used support vector machines which uses clustering to seperate the classes into a feature space and is especially useful when we are dealing with high-demensional datasets