Sentiment_Analysis with python

Sentiment analysis is a common NLP task, which involves classifying texts or parts of texts into a pre-defined sentiment
We will install NLTK and download the sample tweets that we will use to train and test our model this is the corpora And then we will use the negative and positive tweets to train our model.
Then we will make a Normalization which is the process of converting a word to its canonical form.
In Normalization we will make lemmatization to convert word to its normalized form, and then we will clean it from stopwords and punctuations.
We will apply Binarized multinomial naive bayes Algorithm where the frequencies of the words don't play a key role in our calssification.
Then we will use the test data to compute the percentage of how our algorithm make correct detect
We can get sentence and then classify it if it was positive or not