This paper will describe a project created using support vector machines (SVM) to predict stock price. Since the method is support vector machines, the data must be labeled, which fits what needed for stock evaluation. Stock’s information comes from its financial statements, which are all labeled. In this particular project, the version of SVM is a machine called least square support vector machines, which are used for regression analysis. The language being used is Python with scikit-learn, which has SVM implemented in the library.

This paper will describe a project using augmented reality (AR). AR is a live direct or indirect view of a physical, real world environment augmented (or supplemented) by computer-generated sensory input such as sound, video, graphics or GPS data. For this particular project, I will use Swift to implement a iOS app to provide users a augmented reality graphical view with supplemented GPS information. The application will take the user’s location and give additional information about the POI around the areas on the phone when the POI shows up.

This paper will describe a project using Machine Learning for Real-time Face Detection and Recognition using the mobile’s camera and compare the result to college’s student database. The paper will allow people to connect easily by knowing the name, location and mobile number with just a look on the phone. The program will run on iOS and Android using Cordova as a base.