Название: Predictive Analytics for the Modern Enterprise: A Practitioner’s Guide to Designing and Implementing Solutions (Fourth Early Release)Автор: Nooruddin Abbas Ali
Издательство: O’Reilly Media, Inc.
Год: 2023-08-31
Страниц: 210
Язык: английский
Формат: epub (true), mobi
Размер: 10.8 MB
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.
At the time of writing this book, there was a lot of buzz about Artificial Intelligence (AI) and Machine Learning (ML). But how did we get from simple calculations to a chatbot having coherent conversations with other humans? From statistical extrapolation of sales figures to planning stocks based on predicted sales, enterprises have come a long way. This journey from data producing to data consuming and finally data driven is what I explore in this first chapter. Together I want to delve into the details of how data analytics has evolved over time, what is predictive analytics (PA) at its roots and its place in the analytical world. I then go on to discuss its role when it comes to data modeling and Machine Learning and the tools available today that can help us do just that.
What the book will delve deeper into, is predictive analytics and the tools and framework needed to develop predictive functionality within organizations. Let’s begin with Python. Python is an object oriented programming language that has taken the world by storm. Its object oriented nature makes code easy to traverse and understand and its dynamic variable binding means that your variables need not be declared and are automatically assigned data types based on the value assigned to them. These attributes make it ideal for rapid application development, optimizing developer productivity, and reducing time to market for new functionality. Python allows for developing packages and modules so that code can be modular and reusable. Python boasts more than a hundred thousand libraries that allow its users to do all forms of data processing and data visualization. One such very famous library that will be a major part of our discussions is TensorFlow. TensorFlow provides an open source library for performing detailed numeric computations. While Tensorflow with Python gives us a strong foundation on Machine Learning and its use for predictive analytics, it’s worthwhile to explore AI/ML services from major public cloud providers.
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
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