Brain wave is a generic term used to refer to the electrical impulses generated by the neurons or during interaction between them. These impulses also known as Neural Oscillations can be observed by the measuring technique known as Electroencephalogram (EEG). Even though research in the field has been carried out since the 1960s, high level applications using brain waves have not emerged yet. Our objective will be to obtain EEG data for different thinking process and visual stimulus. The primary deterrent while obtaining EEG data is noise. The hardware setup is optimized to acquire the data with minimal interference. After initial data acquisition, filters are applied to reduce the noise and leave relevant data. After noise has been reduced and bandwidth limited, Recurrent Neural Network (RNN) or Support Vector Machine (SVM) classification techniques are applied on the dataset to discreetly identify different wave charts generated due to different stimulus. © 2018 IEEE.