Demo of "Decision trees in Machine learning or why is my server going down? - DEVNET-2658" Cisco Live presentation
Data is loaded and managed using pandas and numpy libraries. After that, sklearn decision tree algorithm is used to make predictions on the testing dataset. Sklearn metrics are leveraged to show the accuracy of the model, and also feature importance and the specific parameters of the tree are explored.
Lastly, graphviz and IPython libraries are used to draw a representation of the model.
The basic concepts of Machine Learning will be explained through example, and you will get insights into which problems can be solved by this technology. Participants will deep dive into Decision Trees, the most intuitive algorithm of Machine Learning. You will learn how to implement decision trees in Python using the built-in libraries and interpret the results. As a key take-away you will be able to implement strategies to mitigate the main causes for a system to fail, and apply predictive maintenance.
