Join Doug Rose for an in-depth discussion in this video Unsupervised learning, part of Artificial Intelligence Foundations: Thinking Machines.
- So, you've seen how artificial neural networks…can tune into different patterns.…Each neuron is like a member in a marching band.…They march in layers, one after the other,…and pass information to the layer behind them.…They tune their instrument…and if it matches the note,…then they strengthen their connection to the next row.…After a few million tries,…your neural network can match any music to the song…that you fed into the first row.…How your marching band actually matches the music…is still a bit of a mystery,…maybe there's one part of the song that's really common.…
As long as there's a match,…then they know that it's the same song.…To anyone outside the band,…it all happens as if it's in a black box.…That being said, humans will still have a role to play.…Let's say that you've been very happy…with how your neural network identifies your songs,…so now you want your marching band…to do something even more impressive.…You want to be able to catagorize any song…that's fed to the bandleaders in the front row.…
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