Learn how to mine data and what to look for in statistics! Dive into the complicated matter of analyzing and mining for data correctly. Forget about intuition or assumptions. Data are facts you can rely on if you draw the right conclusions. Drawing those conclusions requires certain skills and a background in knowledge that leads to the proper steps. This guide will help you along the way by addressing topics such as:The what and why of data mining, and the different applications to business-related topics.Attributes, classifications, datasets, and types of learning you need to understand to fully be aware of what you are dealing with.Data quality and data quantity thoughts.Data mining process steps, including CRISP-DM and SEMMA..Linear, probabilistic, and other models to use in the visualization and analysis of data you have found.Techniques such as clustering, viewing genetic algorithms, and neural networks.Evaluation analysis strategies, classification, and numeric predictionsAnd much more! Curious yet? Then don’t wait and start reading, so you don’t have to remain in the dark. Save yourself the time and learn from what worked for me. I will see you in the first chapter!