Democratised Machine Learning Explained

Democratised Machine Learning Explained

Machine learning is a type of artificial intelligence that provides computers with the ability to learn without being explicitly programmed. Machine learning focuses on the development of computer programs that can teach themselves to grow and change when exposed to new data.

This means that new technologies can actually learn from patterns in the data and having learned them could predict what the future is going to be.  By integrating machine learning to a company’s infrastructure, routine work is reduced, and the business becomes more strategic and productive.

Therefore, machine learning can be a crucial component in digital transformation by enabling organisations to exploit their growing data to improve key business and operational use cases.

Democratising Machine Learning is to make it accessible to everyone. It means putting wrappers around it to make sure that this technology is available to people who wouldn’t normally have access to it. Everything that is needed, including gathering data, doing pattern recognition, looking for patterns, sending out alerts, all of these are encapsulated in easy to use platforms.

This functionality should be put together to fit in with the work processes and with the skill set that companies already have in place to ensure that it is as easy as possible to implement, and once done it should be sustainable.  Because of the tremendous potential of machine learning, it is essential to make it available to everyone. Individuals with the eagerness and intelligence required to advance machine learning or to use AI to create great things can come from anywhere. Hence, there is a need to make sure that these people can readily access the tools and information that they need.

If a company is to keep pace with digitalisation, they need to get much better at applying the advances in machine learning to the huge data volumes and processes they manage. The goal is to make better and faster business decisions and to make more money.

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