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Linear regression is one of the simplest machine learning algorithms. But also quite useful. It takes a bunch of existing, known observations and tries to predict how new observations will look like. Think about forecasting or finding trends. It says “ linear ” because the algorithm essentially finds a straight line that most closely follows the observations. OK, let’s take a concrete example. Imagine you are selling your apartment. What is the right price for it? Well, you compare it to similar apartments in your neighborhood. If someone sells the exact same flat across the street, your price should be very similar. If another flat is sold, but 10% larger, expect its price to be 10% higher as well. Yet another flat is half the size of yours. So expect its price to be just 50% of your estimated asking price. Sounds reasonable?
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Jest to odcinek podkastu:
Around IT in 256 seconds
Podcast for developers, testers, SREs... and their managers. I explain complex and convoluted technologies in a clear way, avoiding buzzwords and hype. Never longer than 4 minutes and 16 seconds. Because software development does not require hours of lectures, dev advocates' slide decks and hand waving. For those of you, who want to combat FOMO, while brushing your teeth. 256 seconds is plenty of time. If I can't explain something within this time frame, it's either too complex, or I don't understand it myself.
By Tomasz Nurkiewicz. Java Champion, CTO, trainer, O'Reilly author, blogger
Kategorie:
Technologia
Technologia