Predictive Analytics for the Modern Enterprise : A Practitioner's Guide to Designing and Implementing Solutions

Predictive Analytics for the Modern Enterprise : A Practitioner's Guide to Designing and Implementing SolutionsThe surging predictive analytics market is expected to grow from $10. 5 billion today to $28 billion by 2026. With the rise in automation across industries, the increase in data driven decision making, and the proliferation of IoT devices, predictive analytics has become an operational necessity in today's forward thinking companies. If you're a data professional, you need to be aligned with your company's business activities more than ever before.

The surging predictive analytics market is expected to grow from $10.5 billion today to $28 billion by 2026. With the rise in automation across industries, the increase in data-driven decision-making, and the proliferation of IoT devices, predictive analytics has become an operational necessity in today's forward-thinking companies. If you're a data professional, you need to be aligned with your company's business activities more than ever before. This practical book provides the background, tools, and best practices necessary to help you design, implement, and operationalize predictive analytics in the cloud. Author Nooruddin Abbas Ali, principal solutions architect at MongoDB, brings you up to speed through industry use cases and end-to-end hands-on examples. This book helps business technology leaders: Implement and operationalize predictive analytics in your organization Explore ways that predictive analytics can provide direct input back to your business Understand mathematical tools commonly used in predictive analytics Learn the development frameworks used in predictive analytics applications Appreciate the role of predictive analytics in the machine learning process Examine industry implementations of predictive analytics Build, train, and retrain predictive models using Python and TensorFlow