Learning a new modeling framework is time consuming, and doesn’t always pay off. However, as more feature engineering and modeling frameworks become available, its difficult not to leverage their abilities. Only interested in frameworks available in R? Need a large selection of clustering and regression algorithms? Limiting your train data set because your framework is bursting at the seams?
We’ll cover an in depth overview of the strengths, weaknesses and design logic of the top feature engineering and modeling frameworks available, and which of these frameworks justify pushing through the learning curve.