The volume, diversity, and speed of data available has never been greater. Powerful machine learning methods can unlock the value in this information by finding complex relationships and unanticipated trends. Using the Python programming language, analysts can use these sophisticated methods to build scalable analytic applications to deliver insights that are of tremendous value to their organizations.

In Mastering Predictive Analytics with Python, you will work through a step-by-step process to turn raw data into powerful insights. Power-packed with case studies and code examples using popular open-source Python libraries, this volume illustrates the complete development process for analytic applications. The detailed examples illustrate robust and scalable applications for common use cases. You will learn to quickly apply these methods to your own data.

Covering a wide range of algorithms for classification, regression, clustering, and cutting-edge techniques such as deep learning, you will learn not only how these methods work, but how to implement them in practice. You will also gain the skill to choose the right approach for your problem. This guide also explains how to develop engaging visualizations from these algorithms, to bring the insights of predictive modeling to life for the analyst and their stakeholders.