Q: What are some of the common use cases of natural language processing?
A: Natural Language processing is branch of Machine learning algorithms that process text data to produce meaningful insights. A few of the common use cases of NLP are answering questions asked by the user, sentimental analysis, language translation to a foreign language, search engines, and document classifications. The key point to understand here is that if you want to perform analytics/machine learning on data represented by text/sentences/word format, NLP is the way to go.
Q: How is feature extraction relevant to NLP?
A: Machine learning algorithms work on mathematical forms. Any other forms, such as Text, need to be converted into mathematical forms to apply machine learning algorithms. Feature extraction is converting forms, such as texts/images, into numerical features, such as Vectors. These numerical features act as an input to Machine learning algorithms. Techniques such as TF-IDF...