Automated Machine Learning for Business R. Larsen

Automated Machine Learning for Business – Ebook Instant Download/Delivery ISBN(s): 9780190941666,0190941669

Product details:

• ISBN-10 ‏ : ‎ 0190941669
• ISBN-13 ‏ : ‎ 978-0190941666
• Author: R. Larsen, Kai, Becker, Daniel S.

Though the concept of computers learning to solve a problem may still conjure thoughts of futuristic artificial intelligence, the reality is that machine learning algorithms now exist within most major software, including Websites and even word processors. These algorithms are transforming society in the most radical way since the Industrial Revolution, primarily through automating tasks such as deciding which users to advertise to, which machines are likely to break down, and which stock to buy and sell. While this work no longer always requires advanced technical expertise, it is crucial that practitioners and students alike understand the world of machine learning.

Table contents:

Section I: Why Use Automated Machine Learning?
1. What Is Machine Learning?

2. Automating Machine Learning

Section II: Defining Project Objectives
3. Specify Business Problem

4. Acquire Subject Matter Expertise

5. Define Prediction Target

6. Decide on Unit of Analysis

7. Success, Risk, and Continuation

Section III: Acquire and Integrate Data
8. Accessing and Storing Data

9. Data Integration

10. Data Transformations

11. Summarization

12. Data Reduction and Splitting

Section IV: Model Data
13. Startup Processes

14. Feature Understanding and Selection

15. Build Candidate Models

16. Understanding the Process

17. Evaluate Model Performance

18. Comparing Model Pairs

Section V: Interpret and Communicate
19. Interpret Model

20. Communicate Model Insights

Section VI: Implement, Document and Maintain
21. Set Up Prediction System

22. Document Modeling Process for Reproducibility

25. Time-Aware Modeling

26. Time-Series Modeling

Appendix B. Optimization and Sorting Measures
Appendix C. More on Cross Validation
References
Index

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