This thesis addresses the issue of recognizing the hand signs of American Sign Language utilizing deep learning artificial intelligence techniques. The recognition rates of sample data was measured after sample data was prepared in one of three ways: normalizing the image, coverting to binary black and white, and color with background removed. Of the three, this thesis showed that recognition is best with color and background removed.