Real World Projects:Build & Deploy Machine Learning Web Apps

Machine learning is not like any other technology, but it is in many cases the only technology that can solve certain problems. We need to ensure that all people involved in the project have a common understanding of what is required, how the process works, and that we have a realistic view of what is possible with the tools at hand. To boil down all this to its core components we could consider a few important rules:

create a common ground of understanding, this will ensure the right mindset

state early how progress should be measured

communicate clearly how different machine learning concepts works

acknowledge and consider the inherited uncertainty, it is part of the process

An easy example of a machine learning algorithm is an on–demand music streaming service. For the service to make a decision about which new songs or artists to recommend to a listener, machine learning algorithms associate the listener s preferences with other listeners who have a similar musical taste. This technique, which is often simply touted as AI, is used in many services that offer automated recommendations.

Machine learning fuels all sorts of automated tasks that span across multiple industries, from data security firms that hunt down malware to finance professionals who want alerts for favorable trades. The AI algorithms are programmed to constantly be learning in a way that simulates as a virtual personal assistant something that they do quite well.