Sentiment:
In normal language usage, the noun "feeling" is often used as being the same as emotion. On other words to understans Sentiment analysis is that, we can go through Amazon product reviews, if you want to purchase graphis card from amazon you will search for that product.
You might see many product searches in one click, buy why the most reviews product came on the top? Compare to others...* Becuase that first product is highly review. The comment that are given by customers that are become sentiment analysis for us. many of positive and many of negative reviews.
sent_1 = Positive | sent_2 = Negative |
___ from the lines and given words we will make a model that output will be Pos-Neg. Suppose we given a sentence: went to this restaurant yesterday and i really loved the food, though they took a while to serve me!___ Now, the model will take this sentence and will give positve or negative output.
how the model will treat this input: In the images we have pixes at it store in 0 and 1 manner. Same in the NLP the deep learning model store in that manner. There are in different way: Standardization Tokenization Encoding For the data I would be like from IMDB Dataset of 50K Movie Reviews;