Predictive Analytics Using R and Python

Catalog description

Introduces the end-to-end data-driven predictive modeling approach in R, Python, KNIME and WEKA with applications and case studies. Includes all the data and modeling steps in a full modeling cycle (training, validation and testing), exploratory data analysis and data cleansing, commonly applied modeling techniques such as SVM, random forest and ensemble models; introduces neural networks using TensorFlow.