Cloud computing is the delivery of computing services—including servers, storage, databases, networking, software, analytics, intelligence, and the Internet of Things (IoT)—over the Internet ("the cloud") to offer faster innovation, flexible resources, and economies of scale. Cloud computing is essential for big data processing and many AI applications.

Cloud computing provides the scalable computing resources and storage that are needed to train and deploy DL models. It also provides a variety of tools and services that can be used to manage and analyze big data.

Here is an example of how DL, big data, and cloud computing can be used together to solve a real-world problem:

A company wants to develop a system to detect fraudulent transactions. The company has a large dataset of historical transactions, which includes both fraudulent and legitimate transactions. The company can use cloud computing to train a DL model on this dataset. The trained DL model can then be used to detect fraudulent transactions in real time.

The company can deploy the DL model in the cloud as a service. This allows the company to scale the system up or down as needed, and it also allows the company to access the system from anywhere in the world.

In this example, DL is used to learn complex patterns from the data that would be difficult or impossible for traditional ML algorithms to learn. Big data is used to train the DL model on a large dataset of historical transactions. Cloud computing is used to provide the scalable computing resources and storage that are needed to train and deploy the DL model.

DL, big data, and cloud computing are three powerful technologies that are being used to solve a wide variety of problems in the real world.