From the course: Artificial Intelligence Foundations: Machine Learning

Exploring machine learning

From the course: Artificial Intelligence Foundations: Machine Learning

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Exploring machine learning

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- [Narrator] What is artificial intelligence, or AI, and how does it impact you? Simply put, AI is the simulation of human intelligence by machines. Well, how does this machine learning relate to AI? Machine learning is a subset of AI that applies mathematics to large datasets to find trends and patterns while mapping inputs to outputs. Such as, given these features of a home, age, location, and the number of bedrooms as input, what will the selling price be? This means computers can produce output without being explicitly programmed by a developer or software engineer. The mappings uncovered between the inputs and outputs are stored in a mathematical model, simply called the model. Models are often depicted as a brain because they are meant to simulate human intelligence. Machine learning and the algorithms used in machine learning have been around since the 1950s, but suddenly, there's a mass resurgence. Why? Where did this newfound excitement and buzz around machine learning come from? Well, I call it the perfect storm, big data, which brings easier access to the large datasets needed to train machine learning models, and the cloud, which brings accessibility with easy-to-use machine learning services and access to powerful compute power, like GPUs at the click of a button. Because of this perfect storm, the use of machine learning is widespread. Take a moment and think about how machine learning already touches your life daily. Which movie will you watch on your favorite streaming platform? Will you default on the auto loan you're applying for? Is your most recent debit card transaction fraudulent? Will you become one of the local coffee shop's most loyal customers? Who are you? I see you're a Sky Miles member. How can I help you today? These are all questions machines can answer. I can bet I know what you're thinking. First, you're thinking, "Wow, machine learning is widespread." Next, you remember that I mentioned the word mathematics at least twice, and you know that math can be scary. Don't worry. You don't need a PhD in mathematics to excel in machine learning. You'll do just fine if you understand linear algebra, basic equations and probability. Basic knowledge of programming and Python will help you understand the hands-on labs, but have no fear. I'll show you widely used libraries that do the heavy lifting for you. Bring your curiosity, intuition around inputs and outputs and real world problems to solve, and you'll do fine in this course.

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