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Paragraph 1: Machine learning algorithms can be applied on lloT to reap the rewards of cost savings, improved time, and performance. In the recent era we all have experienced the benefits of machine learning techniques from streaming movie services that recommend titles to watch based on viewing habits to monitor fraudulent activity based on spending pattern of the customers. It can handle large and complex information to draw interesting patterns or trends in them such as anomalies. Machines are needed to process information fast and make decisions when it reaches the threshold. Paragraph 2: Machine learning is here. Artificial intelligence is here. We are right in the midst of the information revolution and while it's an incredible time and place to be in, one must be wary of the implications that come along with it. Having a machine tell you how long your commute will be, what music you should listen to, and what content you would likely engage with are all relatively harmless examples. But while you're scrolling through your Facebook newsfeed, an algorithm somewhere is used to make decisions about someone's medical diagnoses, their parole eligibility, or their career prospects. What is the cosine-similarity between Paragraph 1 and itself? Prove your answer.

Paragraph 1: Machine learning algorithms can be applied on lloT to reap the rewards of cost savings, improved time, and performance. In the recent era we all have experienced the benefits of machine learning techniques from streaming movie services that recommend titles to watch based on viewing habits to monitor fraudulent activity based on spending pattern of the customers. It can handle large and complex information to draw interesting patterns or trends in them such as anomalies. Machines are needed to process information fast and make decisions when it reaches the threshold. Paragraph 2: Machine learning is here. Artificial intelligence is here. We are right in the midst of the information revolution and while it's an incredible time and place to be in, one must be wary of the implications that come along with it. Having a machine tell you how long your commute will be, what music you should listen to, and what content you would likely engage with are all relatively harmless examples. But while you're scrolling through your Facebook newsfeed, an algorithm somewhere is used to make decisions about someone's medical diagnoses, their parole eligibility, or their career prospects. What is the cosine-similarity between Paragraph 1 and itself? Prove your answer.

Database System Concepts
Database System Concepts
7th Edition
ISBN:9780078022159
Author:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan
Publisher:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan
Chapter1: Introduction
Section: Chapter Questions
Problem 1PE
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Paragraph 1: Machine learning algorithms can be applied on lloT to reap the rewards of cost savings, improved time, and performance. In the recent era we all have experienced the benefits of machine learning techniques from streaming movie services that recommend titles to watch based on viewing habits to monitor fraudulent activity based on spending pattern of the customers. It can handle large and complex information to draw interesting patterns or trends in them such as anomalies. Machines are needed to process information fast and make decisions when it reaches the threshold. Paragraph 2: Machine learning is here. Artificial intelligence is here. We are right in the midst of the information revolution and while it's an incredible time and place to be in, one must be wary of the implications that come along with it. Having a machine tell you how long your commute will be, what music you should listen to, and what content you would likely engage with are all relatively harmless examples. But while you're scrolling through your Facebook newsfeed, an algorithm somewhere is used to make decisions about someone's medical diagnoses, their parole eligibility, or their career prospects. What is the cosine-similarity between Paragraph 1 and itself? Prove your answer.
Transcribed Image Text:Paragraph 1: Machine learning algorithms can be applied on lloT to reap the rewards of cost savings, improved time, and performance. In the recent era we all have experienced the benefits of machine learning techniques from streaming movie services that recommend titles to watch based on viewing habits to monitor fraudulent activity based on spending pattern of the customers. It can handle large and complex information to draw interesting patterns or trends in them such as anomalies. Machines are needed to process information fast and make decisions when it reaches the threshold. Paragraph 2: Machine learning is here. Artificial intelligence is here. We are right in the midst of the information revolution and while it's an incredible time and place to be in, one must be wary of the implications that come along with it. Having a machine tell you how long your commute will be, what music you should listen to, and what content you would likely engage with are all relatively harmless examples. But while you're scrolling through your Facebook newsfeed, an algorithm somewhere is used to make decisions about someone's medical diagnoses, their parole eligibility, or their career prospects. What is the cosine-similarity between Paragraph 1 and itself? Prove your answer.
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