Machine Learning

Last week we learnt about Artificial Intelligence. Machine learning is a subfield of Artificial Intelligence that focuses on the design of systems that can learn from and make decision and predictions based on data. Machine Learning or ML will help computers to make data-driven decisions rather than waiting for a command to carry out a task. Machine Learning systems are designed so that they improve their model over time when they accumulate more data.

For example, you might like to have your computer recognize your images automatically. To do so, you can provide your computer a training set of photos, with labels which say, “this is a dog” or “this is not a dog”. Then you can test your computer with a new set of photos and the trained ML model will help identify which photos are actually dogs and which are not. This is very similar to how we teach a child to recognize animals or any object. Every photo the model identifies correctly gets added to the training set and the ML model gets “smarter” effectively. In short, it is learning.

Healthcare is a popular area for applying Machine Learning. For example, the ML models can help process your medical history data and spot patterns from the complex data much faster than the human doctors. This will help predict any risk factors or health conditions that you can develop in the near future.

This post was also published in the “Tech Jargon of the Week” column in The Campbell Express.