Recently, I purchased a book from Amazon about machine learning here. titled “Hands-On Machine Learning.” I am amazed to have found a 5-star rated book on this topic with over 1000 ratings. Anytime I see a book rated 5 stars, I always want to take a look at it. I found most books to be rated at 4.5 stars. I have read the first chapter, and so far I have found it to be very interesting and useful. I have been brainstorming more uses for machine learning, and I would like to share some of them here. Although I have not yet done a lot of research on these ideas, I have been thinking about them.
Sorting: A machine learning algorithm could be used to sort elements with a certain percentage of accuracy. This is only useful for applications where the list does not need to be in perfect order. However, it may be able to have great speed. Here is a paper talking about using machine learning for sorting. I think if machine learning algorithms can create a faster algorithm for sorting, it could be a big deal because so many applications use sorting. It is one of the most fundamental parts of computer science.
Random Number Generation: It is not easy for a computer to generate truly random numbers. This is very important for cryptography in key generation. Many random number algorithms are not truly random, but useful information such as the computer’s time in milliseconds, or other physical properties of the computer. This application of machine learning can help in cybersecurity.
Video Games: I think that if machine learning is used creatively, it can be used to create very innovative video games. They can be used to create a very difficult challenge, but not too difficult. I think the difficulty should be barely below the player’s skill level to optimize player achievement and satisfaction from the effort. If they are always losing, it would become discouraging, and if they win too frequently, it becomes mundane and boring. I think video games should be exciting, but not impossibly difficult.
Education: Used to help people study by analyzing their study times, test performances, papers, and other metrics related to education. I think this could even be used to help predict careers people will be most satisfied with. However, I don’t think it should be used to help people find out how to make the most money because that is not as important as job satisfaction.
Psychology: Similar to education, but used to understand people’s personalities better.
I am guessing that it is normal for people to think of many different applications that can be solved using machine learning when they begin studying it. I need to remind myself that machine learning, although very powerful, has its limitations too. It almost seems endless the number of applications for machine learning.