Identifying Behaviour Patterns using Machine Learning Techniques
MP4 | Video: AVC 1280x720 | Audio: AAC 44KHz 2ch | Duration: 1 Hour 12M | 237 MB
Genre: eLearning | Language: English

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.
Next, we can analyze users behavior and capture patterns on which we are able to react properly.

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
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
that.

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
find the transition with highest probability.




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