![]() The easiest way to think about artificial intelligence, machine learning, deep learning and neural networks is to think of them as a series of AI systems from largest to smallest, each encompassing the next.Īrtificial intelligence is the overarching system. How do artificial intelligence, machine learning, deep learning and neural networks relate to each other? This blog post will clarify some of the ambiguity. While artificial intelligence (AI), machine learning (ML), deep learning and neural networks are related technologies, the terms are often used interchangeably, which frequently leads to confusion about their differences. You can see its application in social media (through object recognition in photos) or in talking directly to devices (like Alexa or Siri). To keep up with the pace of consumer expectations, companies are relying more heavily on machine learning algorithms to make things easier. ![]() Technology is becoming more embedded in our daily lives by the minute. ![]() Thanks for watching, and we'll see you in the next video.These computer science terms are often used interchangeably, but what differences make each a unique technology? And if your stats teacher is boring or just doesn't care to help you learn stats, go to where you can find out more about accessing our lecture videos or provide feedback on what you'd like to see. Be sure to leave your comments below and let us know how good a job we did or how we can improve. Nice work!Īnd that's how we do it at Aspire Mountain Academy. So therefore we're gonna conclude that it's not close to the actual mean because we're more than five percent off. Divide by the actual 52.8, multiply by 100, and as you can see, we're at 9.1%, which is greater than that 5% threshold. So we're gonna take the actual mean 52.8 - excuse me, 58.2 - subtract out the computed mean (52.9). 52.9 is the calculated or computed mean, 52.8 - excuse me, 52.8 degrees listed here in the problem statement is the actual mean. So if I come back here to my calculator - clear that out - let's compute the actual difference so we know we're looking at. If you want, you could actually calculate the averages like we were doing with the first two bins, but you'll come out with these numbers here.Īnd now, the second part of the problem: Which of the following best describes the relationship between the computed mean and the actual mean? So if we look at our answer options here, the computed mean is either close or not close to the actual mean, and then the difference is being compared to five percent, so we’re either more than five percent or less than five percent. So I can just go ahead and just add five to each one of these midpoints here to get the rest for my table. You can see they're also separated by five. Now if you notice, 47 is five more than 42, and that's because 45, the lower limit for the second class, is five more than 40, which is the lower limit for the first class. ![]() ![]() Punch that out - 49 plus 45 divided by 2 is 47. I'm gonna do it again for the next class. I'm just going to take the average of my upper and lower class limits for that first class there. So we have to actually calculate out here in another column what the actual frequency midpoints are going to be. What we have listed here are actually the lower and upper class limits for each of our bins, so that's not going to help us with StatCrunch. And the way we can do this really easy in StatCrunch requires us to have first midpoints for each of the classes. So we have our data here in StatCrunch, but notice these are frequency counts. ![]()
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