Learn about data vs. reasoning.
- Even though symbolic reasoning, machine learning,…and artificial neural networks are all very different,…they're still considered part of AI.…That means if you're starting an AI project,…you might have to figure out…which one of these approaches works best.…Symbolic reasoning can perform well…if you have an abstract problem,…but also know the steps to find a solution.…Machine learning is useful…when you have to tinker to get the solution.…You don't really know the steps…and you have to look for larger patterns…to come up with the likeliest answer.…
This approach requires several iterations…to arrive at a conclusion.…Some researchers even mix these two approaches.…They use symbolic reasoning to come up with some constraints…and then use machine learning…to experiment with different answers.…When you start your project,…you'll have to decide which approach would work best.…You might even try to balance the two.…Think of it this way.…Let's take something like a ceiling fan.…Kids and adults alike can easily recognize one.…
This course will introduce you to some of the key concepts behind artificial intelligence, including the differences between "strong" and "weak" AI. You'll see how AI has created questions around what it means to be intelligent and how much trust we should put in machines. Instructor Doug Rose explains the different approaches to AI, including machine learning and deep learning, and the practical uses for new AI-enhanced technologies. Plus, learn how to integrate AI with other technology, such as big data, and avoid some common pitfalls associated with programming AI.
- The history of AI
- Machine learning
- Technical approaches to AI
- AI in robotics
- Integrating AI with big data
- Avoiding pitfalls