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Complicated scenarios often require complex algorithms to fully understand what is happening. However, algorithms are limited in the complexity with which they can be applied. The issue is that, when predicting something complex, you will be tempted to add variables until the algorithm can fully explain your data. This includes explaining the errors in the data. However, doing this is problematic as it leads to something called over-fitting. You have made the model highly complicated and specific to the data you are using. Hence, it cannot be applied flexibly to other data.
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MORE IDEAS ON THIS
Algorithms let us go for ‘good enough’ rather than always striving for perfection. If we consistently use algorithms in our lives, we will benefit greatly and can start to relax more. Our brains are built like computers. Therefore, like computers, we should start complementing them with algorithm...
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This one hopes to prevent the overload from happening. It determines the max. amount of data a network can handle. It starts by only sending one package of data. Then, if this is fine, it sends double the amount. It continues this process until it reaches the point of overload.
This can b...
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Even the best strategy sometimes yields bad results—which is why computer scientists take care to distinguish between “process” and “outcome.” If you followed the best possible process, then you’ve done all you can, and you shouldn’t blame yourself if things didn’t go ...
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Finally, the merge sort method involves dividing everything into multiple piles. Each pile should be sorted from A to Z. Then, these piles should be merged.
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The insertion sort method is far more efficient if you have to sort a substantial amount of items. If you consider the book analogy again, the insertion sort method would involve taking all the books off the shelf. Then, placing them back one-by-one, ensuring that the books are placed in the corr...
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The authors of this book suggest that the Optimal Stopping Algorithm is the solution to this. If there are 100 options, this algorithm will state that you should look at the first 37 without taking any of them. Use these first 37 as a standard. Subsequently, whichever item meets these standards s...
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Finally, the merge sort method involves dividing everything into multiple piles. Each pile should be sorted from A to Z. Then, these piles should be merged.
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Thrashing is a very recognizable human state. If you’ve ever had a moment where you wanted to stop doing everything just to have the chance to write down everything you were supposed to be doing, but couldn’t spare the time, you’ve thrashed.
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Predicting probable outcomes is viable when using the correct algorithms.
Predicting probable outcomes based on algorithms dates back to 18th century England. Reverend Thomas Bayes developed a simple way of predicting future outcomes. The authors of this book apply Bayes’ theorem to lotte...
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If you want to be a good intuitive Bayesian—if you want to naturally make good predictions, without having to think about what kind of prediction rule is appropriate—you need to protect your priors. Counterintuitively, that might mean turning off the news.
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This was the first method created. This solution involved sending multiple messengers with the hope that one would slip through undetected. However, sending too many messengers can lead to an overload. With regard to computers, this would be a server overload.
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The greater the uncertainty, the bigger the gap between what you can measure and what matters, the more you should watch out for overfitting – that is, the more you should prefer simplicity.
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Data overload is often considered in relation to a classic thought experiment. In this thought experiment, two generals are preparing to launch a joint attack on a city. This city is located in a fortified valley. These generals are on the two hills either side of the valley. So, the only way the...
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As with many things, the more information you have, the more precise you will be. One method that utilizes vast amounts of information to predict future outcomes is the phenomenon’s distribution pattern. Other names for this distribution are the normal distribution or bell curve. If something is ...
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If a server overload is created, then exponential back-off is a method that should work. Instead of frantically hitting refresh, you could wait a few minutes for the traffic to ease. The exponential part relates to how long you wait between refreshes. The authors suggest waiting twice as long eac...
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Unless we’re willing to spend eons striving for perfection every time we encounter a hitch, hard problems demand that instead of spinning our tires we imagine easier versions and tackle those first. When applied correctly, this is not just wishful thinking, not fantasy...
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As well as advising us on when we should stop searching, algorithms can also tell us when to explore something new. In the book, the authors give the example of a slot machine. Some people will just sit at the machine until they win. However, there is always a thought in people’s minds whether th...
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As well as telling us how to conduct a task step-by-step, algorithms can tell us when to stop doing a task. As humans, we struggle to know when to stop searching for something. Additionally, we have cognitive biases that impact our choices when searching.
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Scheduling our lives can be highly complex and is often a daily challenge. As well as work demands, multiple other life demands make fitting everything difficult. However, some algorithms can help improve how you schedule your life.
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Most people associate algorithms with computers and other forms of technology. However, the word actually dates back to the ninth century. The Persian mathematician, Muhammad Al-Khwarizmi, is the first person to use the word ‘algorithm.’ However, the use of concepts like algorithms dates back to ...
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The authors of this book explain that organized chaos can be fine. As long as you know where everything is, you will be productive. However, if your filing system is not efficiently organized, there are algorithms to improve your organization.
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Some of the biggest challenges faced by computers and human minds alike: how to manage finite space, finite time, limited attention, unknown unknowns, incomplete information, and an unforeseeable future; how to do so with grace and confidence; and how to do so in a com...
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Algorithms to Live By offers shortcuts and hacks to help streamline your life. Algorithms are inserted into computers and other forms of technology to solve problems. However, there is no reason that we cannot use algorithms in our everyday liv...
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Compelling and entertaining, Algorithms to Live By is packed with practical advice about how to use time, space, and effort more efficiently. And it's a fascinating exploration of the workings of computer science and the human mind
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