Overview: Covers the parametric, ensemble, and the non-parametric methods.Presents techniques to improve model performance in pre- and post-training.Summarizes H2O driverless AI and automatic forecasting using .Get insight into data science techniques such as data engineering and visualization, statistical modeling, machine learning, and deep learning. This book teaches you how to select variables, optimize hyper parameters, develop pipelines, and train, test, and validate machine and deep learning models. Each chapter includes a set of examples allowing you to understand the concepts, assumpt
|