Mr John is a stock trader. He is into buying and selling stocks to make profit. Ideally, he would want to buy stocks when the prices are low and sell when the prices rise. He has approached you, as a machine learning engineer to build a model that will predict stock prices for him to make decision buy/sell decisions. He has given you a historic dataset that consists of date, open day price, highest price of the day. Lowest price of the day, closing day price, volume and the output/target variable is the price direction (up or down).

1. Which type of machine learning is suitable for building the above mentioned model? Justify your answer.
2. Briefly describe 5 application areas where this machine learning approach can be used in real world applications.