April 2018
Beginner to intermediate
566 pages
12h 17m
English
Chapter 1, Credit Risk Modeling, builds the predictive analytics model to help us to predict whether the customer will default the loan or not. We will be using outlier detection, feature transformation, ensemble machine learning algorithms, and so on to get the best possible solution.
Chapter 2, Stock Market Price Prediction, builds a model to predict the stock index price based on a historical dataset. We will use neural networks to get the best possible solution.
Chapter 3, Customer Analytics, explores how to build customer segmentation so that marketing campaigns can be done optimally. Using various machine learning algorithms such as K-nearest neighbor, random forest, and so on, we can build the base-line approach. ...