APPLICATION OF SUPERVISED LEARNING
DEEP LEARNING
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Question
[CLICK ON ANY CHOICE TO KNOW THE RIGHT ANSWER]
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One to one
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One to many
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Many to one
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Many to many
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Detailed explanation-1: -Many-to-Many: Many-to-many sequence problems involve a sequence input and a sequence output. For instance, stock prices of 7 days as input and stock prices of next 7 days as outputs. Chatbots are also an example of many-to-many sequence problems where a text sequence is an input and another text sequence is the output.
Detailed explanation-2: -Sentiment analysis (or opinion mining) is a natural language processing (NLP) technique used to determine whether data is positive, negative or neutral. Sentiment analysis is often performed on textual data to help businesses monitor brand and product sentiment in customer feedback, and understand customer needs.
Detailed explanation-3: -Sentiment analysis is used to determine whether a given text contains negative, positive, or neutral emotions. It’s a form of text analytics that uses natural language processing (NLP) and machine learning. Sentiment analysis is also known as “opinion mining” or “emotion artificial intelligence”.