Applications of NLP

The video discusses the significance of Natural Language Processing (NLP) in analyzing unstructured data, which constitutes a large portion of industry data. It highlights various applications of NLP, such as sentiment analysis, chatbots, and machine translation, with examples like Twitter, Facebook, and Google Translate. The video also introduces fundamental NLP tasks, including tokenization, stemming, and lemmatization, and mentions that tokenization will be covered in the next video.

What percentage of industry data was unstructured in 2020?

• 80%

• 70%

• 60%

• 50%

Which social media platforms use sentiment analysis as an application of NLP?

• Snapchat and TikTok

• Instagram and LinkedIn

• Twitter and Facebook

• Pinterest and Reddit

What is a common example of machine translation using NLP?

• Google Translate

• Microsoft Word

• Apple Siri

• Amazon Alexa

Which of the following is NOT a fundamental NLP task?

• Tokenization

• Stemming

• Data Mining

• Lemmatization

What NLP task will be focused on in the upcoming project?

• Chunking

• Stemming

• Tokenization

• Named Entity Recognition