According to Arthur Samuel (1959), Machine Learning (ML) is a field of scientific study that empowers a computer the ability to learn and act without being explicitly programmed. ML is a subset of Artificial Intelligence (AI), which involves more specific algorithm and advanced technique that enables our computer to think like human as well as in decision making. It is so pervasive nowadays and sometimes we are even unable to notice its existence for any application we have used in our daily life such as microwave (refer to IoTs). Over the past two decades, AI technology has been booming in each and every part of industry, with no doubt, we believe financial industry is the most pervasive among the others, as each nanosecond in financial market nowadays matters in being “cutting edge” especially in High Frequency Trading (HFT), which empower the computerized trading algorithm to gain from any riskless arbitrage (or opportunity) with the unparalleled edge over the speed and accuracy that any human could not surpass. What we are eagerly to solve here is the similar headache of investor (or trader) as we’ve encountered before, over data collecting (e.g. news) and analyzing information (e.g. statistical tools) for determining any investment opportunity (low risk, high return) in the financial market as well as, attached with customization support to any specific need of what our users desire to, at lowest cost as we could provide, with the extensive coverage to Mobile Apps (Coming Soon) for being kept up-to-date at anywhere and anytime.