Digitization has dramatically transformed the world we live in, where network ecosystems form an essential part of our lives, from existing in the simplest form as home network to the highly complex network the Internet. When we take a look at even the simplest network ecosystem, it has multiple users, variety of devices, numerous protocols and varied uses; making it inherently complex to understand. In addition to these invariants the ever-evolving nature of networks, constantly emerging newer network attacks and unethical usage of network traffic has made Network Security of fundamental importance. In order to efficiently combat security issues, it is vital to understand the network traffic and its behavior. This can be done efficiently through the process of Network Traffic Analysis where network traffic data is recorded and then analyzed for patterns to combat security threats. The primary aim of this project is to develop a tool that uses a Machine Learning algorithm to analyze network traffic to create visualizations based on the observations to get a deeper understanding of the network traffic.