#30 - The Art of Feature Engineering: Crafting Input for Machine Learning Models

In this episode of "The AI Frontier," we delve into the fascinating world of feature engineering in machine learning. We start by understanding what feature engineering is and why it's crucial in machine learning. We then explore various techniques for feature engineering, from basic methods like binning and scaling to advanced concepts like automated feature engineering and feature selection. We also discuss how these techniques can be applied to different types of data, including text, images, and time-series data. To bring these concepts to life, we examine a real-world case study that demonstrates the power of feature engineering in improving machine learning models. This episode is a must-listen for anyone interested in machine learning, data science, or AI. Join us as we navigate the art of crafting input for machine learning models.

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References Used in This Episode:

1.    Zhou B, Pychynski T, Reischl M, Kharlamov E, Mikut R. Machine learning with domain knowledge for predictive quality monitoring in resistance spot welding. Journal of Intelligent Manufacturing. 2022. [Link]