Happened on : December 8, 2017, 3:00 pm (IST)

This topic is going to cover Data Science behind Display Advertising. In Display Advertising, marketers want to maximize rewards/clicks by minimizing the cost. This topic will cover the optimization which makes this happen.

Starting with data sources involved, preprocessing steps to make data training ready,  algorithms used for training and metrics to evaluate. The focus will be to dig deep into key variables understand the interaction of variables and how it affects the selection of the algorithm.

Key Takeaways:

• Know the data science problem behind display marketing
• Understand how distributed frameworks like Hadoop MR  can be leveraged to solve  data science problem behind large-scale time critical applications
• Realize the power of feature engineering
• Some guidelines on how to choose ML Algorithm

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