Predictive Analytics for the Modern Enterprise: A Practitioner's Guide to Designing and Implementing Solutions,1st Edition by Nooruddin Abbas Ali

Based on the research, predictive analytics is expanding incredibly fast, with the market increasing from $10. From $5 billion currently, it is forecasted to touch $28 billion by 2026. This is due to the advancement of automation systems, data processing aspects for decision-making, and the development of IoT devices, making predictive analytics crucial for today’s business environment. By employing predictive analytics, companies will be aware of trends and changes and respond to them adequately.

It is consequently even more crucial for an expert in data to anchor her work around the mission and vision of her organization. This book, Predictive Analytics for the Modern Enterprise, holds in readers’ hands all they need to know when it comes to designing and deploying PAM solutions for on-premises and/ or in the cloud environments. It ranges from the introduction of mathematical instruments and development environments to the function of predicting analysis in the machine learning process.

You will also discover the practical uses of predictive analytics in different fields, how to construct and train models, and how to rerotate them using Python and TensorFlow. After reading the book Predictive Analytics for the Modern Enterprise, you will be in a position to use predictive analytics to advance your business and make better decisions, which will, in turn, have a positive influence on your organization.

Predictive Analytics for the Modern Enterprise Table of Contents:

1. Preface
2. Chapter 1: Data Analytics in the Modern Enterprise
3. Chapter 2: Predictive Analytics: An Operational Necessity
4. Chapter 3: The Mathematics and Algorithms Behind Predictive Analytics
5. Chapter 4: Working with Data
6. Chapter 5: Python and scikit-learn for Predictive Analytics
7. Chapter 6: TensorFlow and Keras for Predictive Analytics
8. Chapter 7: Predictive Analytics for Business Problem-Solving
9. Chapter 8: Exploring AWS Cloud Provider Services for AI/ML
10. Chapter 9: Food for Thought

Who is this course for?

1. Data Experts: Enhance your credits in designing and implementing predictive analytics.
2. Business Analysts: Understand how large and small businesses can apply concepts from data analysis and research to create strategies for their companies.
3. IT Specialists: Learn how to implement predictive analytics in traditional and new hybrid models.
4. Machine Learning Fans: Learn about the part played by predictive analytics in the making of machine learning.
5. Industry Professionals: Watch the case study and get to learn how different organizations apply predictive analytics.
6. Developers: Interactive learning to create and retrain models with the help of Python and TensorFlow.

Click on the links below to Download Predictive Analytics for the Modern Enterprise!