Finance is one of the pioneering industries that started using Machine Learning (ML), a subset of Artificial Intelligence (AI) in the early 80s for market prediction. Since then, major firms and hedge funds have adopted machine learning for stock prediction, portfolio optimization, credit lending, stock betting, etc. In this paper, we survey all the different approaches of machine learning that can be incorporated in applied finance. The major motivation behind ML is to draw out the specifics from the available data from different sources and to forecast from it. Different machine learning algorithms has their abilities for predictions and are heavily depended on the number and quality of parameters as input features. This work attempts to provide an extensive and objective walkthrough in the direction of applicability of the machine learning algorithms for financial or stock market prediction.