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.



Assign 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?

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