Conclusion:
This is one example of a sentiment analysis done on a text database. There are several kinds of sentiment analysis techniques available using different algorithms. Even this is not perfect and it is possible to tune the model better. As with all ML algorithms, the accuracy of results depends on our model. The better the model is tuned to our requirements, the better the result. In case of deep learning, the greater the amount of data fed, the greater the accuracy of the neural network. These are the basics of how a simple sentiment analysis is done. For more on this, learn
Sentiment Analysis & Deep Learning from our centers in Kolkata. Our
Deep Learning Kolkata centers can explain more about neural networks and sentiment analysis.