Believe it or not, you’ve just scratched the surface of natural language processing. There are a slew of advanced topics and applications of NLP, many of which rely on deep learning and neural networks.
Naive Bayes classifiers are supervised machine learning algorithms that leverage a probabilistic theorem to make predictions and classifications. They are widely used for sentiment analysis (determining whether a given block of language expresses negative or positive feelings) and spam filtering.
We’ve made enormous gains in machine translation, but even the most advanced translation software using neural networks and LSTM still has far to go in accurately translating between languages.
Some of the most life-altering applications of NLP are focused on improving language accessibility for people with disabilities. Text-to-speech functionality and speech recognition have improved rapidly thanks to neural language models, making digital spaces far more accessible places.
NLP can also be used to detect bias in writing and speech. Feel like a political candidate, book, or news source is biased but can’t put your finger on exactly how? Natural language processing can help you identify the language at issue.
review a string with a brief review of this lesson so far. Next, run your code. Is the Naive Bayes Classifier accurately classifying your review?