From the course: Leveraging Cloud-Based Machine Learning on Google Cloud Platform: Real World Applications

AI processing and Google - Google Cloud Tutorial

From the course: Leveraging Cloud-Based Machine Learning on Google Cloud Platform: Real World Applications

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AI processing and Google

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- [Narrator] So the question becomes, why do machines need to think like us? So there's many different applications out there for machine learning-based systems, such as the ability for ride sharing applications to figure out where you're going to need a ride and make sure they're directing their resources at where the people need them. Ultimately, we see this every day in streaming services, such as those that provide movies and TV shows, to recommend things that we may like, and typically they're right. And then more importantly, the ability for clinicians or doctors or hospitals to spot issues and take early corrective action based on information that's obtained off of your body. So how do things relate ultimately? We do have AI systems and machine learning which is really a part of that. We have deep learning technology. And then ultimately, we're trying to figure out what's next, we have the ability to share knowledge bases, the ability to get smarter and the ability for these things to in essence think on their own and create knowledge bases, they're able to provide more value as we move forward, specifically to business needs. So ultimately the workflow of machine learning are very similar, and we're going to see similar patterns within Google Cloud Platform as we would in Azure or as we would in Amazon Web Services. So we're able to source the data, able to code the model, ultimately train the model as to what the data means. Then take that knowledge base and deploy it, and then leverage that knowledge base to obtain predictions, such as fraud detection, such as clinical analysis. And then we're able to leverage those predictions in transactional ways, we're able to monitor them over time, and make sure that they're providing us with the correct information. Then as anything we have to do when we build something in the cloud, we have to operate it, and make sure that it functions over a long period of time and that it's continually improved.

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