This book will provide you with an in-depth understanding of machine learning, data science, predictive analytics, big data, data analytics, predictive modeling, and the applications of machine learning.
If you are looking to get a head start on your dream career or improve your knowledge as a data scientist, credit risk analyst, credit risk modeler, or data analyst, this is the book for you. It is easy enough for a beginner to understand yet will provide you with a comprehensive understanding of the subject when read cover to cover.
Every single step of building a predictive model is included from selecting the right variables and determining the appropriate type of model, to testing and updating the model. This book contains numerous illustrative case studies and real-life application examples, graphing examples and techniques, and sophisticated thinking skills. Every chapter explains a different facet of machine learning and all of the various tools that one can use as a data scientist.