What is Multi-Task Learning?

Instructor: Lyna Griffin

Lyna has tutored undergraduate Information Management Systems and Database Development. She has a Bachelor's degree in Electrical Engineering and a Masters degree in Information Technology.

In this lesson, we will learn what multi-task learning is about and use related examples to also try and explain its application in our everyday life.

Understanding Multi-Task Learning

Multi-task learning is an approach used to aggregate together similar tasks or problems and train a computer system to learn how to resolve collectively the tasks or problems. This leads to the resolution of more complex tasks or problems within the shortest possible time using machine learning.

For example, Michael is a college student majoring in Electronics Engineering. At the start of his course of study, he attends lectures each day for a single subject during his freshman days in school. It was easier and convenient for him to learn at a slow pace.

However, when Michael began his sophomore year and the topics were becoming more complex, he discovered that learning one subject per day was going to slow down his pace and hopes for graduating on time. It was also affecting his comprehension of other topics which hitherto would have been seamless since some of the subject topics were inter-related and learning one helps complement his understanding of the other. This need continued right up to his final year in college.

Importance of Multi-Task Learning

The scenario painted above is typical of the early days of the computer system. The first generation of computer systems could only handle a single task at a time and depending on how complex the task was, it often required that it was broken down into smaller and simpler bits which were then fed into the computer system and analyzed separately. Each bit of the results is merged into one to give the desired results. Therefore, the outcome could be easily flawed.

However, with the coming of multi-processor computer systems, the handling of many complex tasks became easier as the computer system could now run multiple tasks at the same time to achieve a single result output devoid of errors.

Multi-Task Learning and Application

In multi-task learning, a computer system through its processor is trained to use previous outcomes or historic values or patterns of occurrence to predict similar outcomes using differently sourced or unrelated data.

Now, how is this possible? Referring back to our student Michael, he researched the subjects he needed to complete towards earning a degree. He basically was looking for how related the topics were.

For example, in a Physics course, he discovered he had to learn a bit of Trigonometry. Now his knowledge of this dates back to when he was in High School and he needed to refresh his memory on this to survive. Luckily for him, he's also scheduled for a Mathematics course which happens to include Trigonometry as one of its topics.

If he studies this subject before taking the Physics course, he would be at an advantage, so he took this opportunity and began studying this first before the class which helped him a lot.

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