<p>Nowadays web-sites needs to handle huge amount of traffic. We can leverage that fact and capture user interactions with the application. For further analysis. <br />Next, we can analyze users behavior and capture patterns on which we are able to react properly.</p> <p>In applications that needs to deal with huge amount of traffic it is very hard to detect anomalies. We’ll learn how to apply clustering to find anomalies in web <br />traffic. Next, we can analyze users behaviour and when they tend to do on our application using time series data. We will be using GMM clustering technique to achieve <br />that.</p> <p>On the e-commerce sites we want to predict when and what user wants to buy in the future. We can use the Hidden markov Model to find transitions between states and <br />find the transition with highest probability.</p> <h1>Style and Approach</h1> <p>This course will start with clustering that will help to detect network traffic and analyze users behaviour using time series data using Gaussian Mixture Model. By the <br />end, viewers will be able to predict users behaviour using Hidden Markov Model and understand highest probability.</p>