This talk is part of our Machine Learning education series. In this session we will look at our first logical model – Decision Trees.
Previous talks in this series can be found here.
We will cover topics like organisation of a tree structure, using machine learning to construct decision trees, and employing decision trees to make predictions for classification tasks. We will also introduce metrics like entropy and information gain, and we will talk about advantages and disadvantages of the decision tree model.
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Understanding and Using Decision Trees
Nikolay has over 10 years of database experience and has been involved in large scale migration, consolidation, and data warehouse deployment projects in the UK and abroad. He is a speaker, blogger, author of numerous articles and a book on advanced database topics. For the last three years Nikolay has been working exclusively in the big data (Hadoop) space with focus on Spark and machine learning. He has an M.Sc. in Software Technologies and is working towards an M.Sc. in Data Science.