"99 little bugs in the code, 99 little bugs. Take one down, patch it around, 117 little bugs in the code."
This is the second part of my journey to understand Artificial Intelligence! In this blog post I will discern Machine Learning from Artificial Intelligence and how it's being used in programming!
In my previous blog post, AI For Beginners, I discussed how an AI model relies on the data that is provided in order to find patterns, and how not insufficient data can result in Overfitting. In this blog post I will expand on how an AI model uses Machine Learning to find patterns in complex scenarios that we as humans may not be able to see, and how programming an AI model Differs from traditional programming methods.
At first glance it may seem that Artificial Intelligence and Machine Learning are the same thing, but it is important to distinguish the two in order to understand how Machine Learning works. AI describes a broad field of computer programming that simulates human cognition to complete various tasks. Think of it as an umbrella term that represents all software of the sort. Machine Learning is a specific subset of AI that uses Data Driven Algorithms in order to create models that can preform complex tasks.
Machine Learning depends on two things, Data and Labels. By providing data with corresponding labels programmers are able to create a model where a machine is able identify patterns within the data and assign a label to it. For example lets take the game of tic-tac-toe. If we were to provide examples of various moves and label them as “Good Moves” or “Bad Moves” we could code a Model that would look at the patterns from each move and choose a “Good Move”. Over time this would create a Model that mimics moves a real person would make thus making it Artificial intelligence.
This is all to say that Artificial intelligence is simply a different way to program a computer where instead of traditionally creating rules and instructing a computer on how to complete a task, we program a computer using Machine Learning to write code that matches data to corresponding labels through pattern recognition. Stay with me as in my next blog we will further discuss how programmers are writing code that utilize Machine Learning. Feel free to leave feedback in the comments below!
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