Join Doug Rose for an in-depth discussion in this video Big data, part of Artificial Intelligence Foundations: Thinking Machines.
- You see a lot of crossover between AI and big data.…The term big data is used to describe…a lot of different technologies,…but if you go back to the original report,…you'll see that the authors…weren't thinking of big data as a term.…They really used it more as an adjective.…It's a way to describe a particular problem.…In fact, the first time they used the term,…they called it a big data problem.…That means that the best way to read this…is big data problem,…although most people interpret it as big data problem.…
The important thing is to focus on the problem…and not the data.…Big data is basically saying…that we're collecting more data than we can handle,…that it's much easier now to create data…than it is to store, analyze, and interpret it.…The technology that we had to interpret the data…is falling behind the technology we used to create it.…You should think of big data…as a driver for machine learning.…At its core, big data is about managing and analyzing…massive data sets.…
Remember that machine learning needs these massive data sets…
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