Prediction, according to the Merriam Webster Dictionary, is an art of declaring or indicating in advance, especially forecasting on the basis of observation, experience or of scientific reason. According to the Cambridge dictionary, prediction is a statement about what you think will happen in the future. The prediction is made about the outcome of the future based on a body of evidence. This happens based on prior knowledge or evidence. In statistics, prediction is a conclusion based on statistical inference while in science it is a rigorous and often quantitative analysis of past and present data or events to predict what will happen under certain conditions . Say no to plagiarism. Get a tailor-made essay on “Why violent video games should not be banned”?Get the original essayThe prediction has been applied in virtually every area of ​​our lives; in medical research, engineering, geography, forecasting, finance and markets, sports, gaming, technology, communication, construction, etc. Predictions have come a long way in our daily lives. Amazon, Jumia, Konga predict what else you would like to buy every time you shop. Netflix and other movie sites predict which movie you might want to watch. Google predicts how you will respond to your emails. Match.com and other dating sites even try to predict who you might fall in love with. We can see predictions in homes where children predict when their father will be home, wives predict their husbands' movement. Also in the institution where a professor predicts the grade a student will eventually graduate with based on their current grade and seriousness. These predictions have become part of us and we don't always even notice them anymore. Machine learning was applied to help us with this prediction. Machine learning is a current application of artificial intelligence based on the idea that we should simply be able to give machines access to data and let them learn on their own. Machine learning can process a large data set that humans cannot understand and process at high speed. Machine learning has been around since the 20th century, but it is only just beginning to be used thanks to the powerful computers we now have that are capable of performing it. In the 20th century, there were no powerful computers capable of operating it and even today, only a few computers are capable of operating it correctly and efficiently. Additionally, the availability of big data improves the use of machine learning because the algorithms used in machines need as much big data as possible to be trained for greater accuracy and efficiency. There are three methods used in machine learning: supervised, unsupervised, and reinforced learning. In supervised learning, you train the algorithm with data that contains the answer. Example when you train a machine to identify your friends by name, you need to identify them for the computer. If you have trained an algorithm with data whose pattern you want the machine to discover on its own, this is called unsupervised learning. If you give a machine a goal and expect it to achieve that goal through trial and error, this is called reinforced learning. Few high-profile examples of machine learning applications are: Google's self-driving car, online recommendation offerings..