A: Cloud computing is currently one of the most favorable technologies for machine learning. It uses virtualization to create a copy of the computer system on demand, and provides access to it through the Internet. Data can also be stored on cloud server, which means that it is not necessary to store your data on your own computer. This greatly simplifies data analytics, as data is no longer stored in several places, but instead is available for everyone. This makes cloud computing perfect for machine learning, since it is generally used for large datasets. Cloud computing also makes it possible to work with data from multiple sources at the same time, which leads to even more opportunities.
A: Initialise app engine
App Engine is one of Google’s cloud solutions. It allows anyone to use Google’s infrastructure without having to worry about server administration. App Engine provides users with a web application environment, where they can run their own programs, without having to worry about how it works. App Engine takes care of all technical aspects, such as installation and configuration, security, hosting and storage. An additional benefit is that App Engine allows for easy scaling on demand. If there is more load on the application, App Engine automatically adds more servers. This allows users to focus on their core business functions, instead of dealing with these issues.
Cloud computing has many advantages when it comes to machine learning. It makes it easy to access massive amounts of data, which means that results are obtained faster than they would be otherwise. Data can be accessed from anywhere in the world, which reduces time spent traveling to data centers. It also makes it possible to use data from multiple sources at once, which increases the accuracy of results.