The primary purpose of employing hand gesture detection to control computer applications is to improve user-computer interaction by making computers responsive to users needs. Hand gesture recognition is achieved using non-vision and vision-based techniques. Vision based technique is more natural in general because these do not involve the use of any hand gadgets. Application of our work is to access an PPT(Power Point) without using a keyboard or a mouse, hand motion detection and sign language understanding. This results in enhanced human computer interaction, ease of accessing a computer application and getting rid of difficulties that exist between the user and computer caused due to any hardware damage or failure such as wear and tear of keyboard, mouse or any I/O device. Gaps that have been identified in gesture recognition were limited only to detection of hand gestures, understanding of the sign language, and decreased efficiency under low lighting conditions. However we have aimed to overcome the stated gaps and introduce a novel way of accessing a power point presentation by leveraging concepts and working principle of gesture recognition using machine learning..