Automated Machine Learning for Business

✍ Scribed by Kai R Larsen; Daniel S Becker

• Publisher: Oxford University Press, USA
• Year: 2021
• Tongue: English
• Leaves: 334
• Category: Library

✦ Synopsis

"In this book, we teach the machine learning process using a new development in data science; automated machine learning. AutoML, when implemented properly, makes machine learning accessible to most people because it removes the need for years of experience in the most arcane aspects of data science, such as the math, statistics, and computer science skills required to become a top contender in traditional machine learning. Anyone trained in the use of AutoML can use it to test their ideas and support the quality of those ideas during presentations to management and stakeholder groups. Because the requisite investment is one semester-long undergraduate course rather than a year in a graduate program, these tools will likely become a core component of undergraduate programs, and over time, even the high-school curriculum"--

✦ Table of Contents

Title Pages
Preface
Why Use Automated Machine Learning
Defining Project Objectives
Acquire and Integrate Data
Model Data
Interpret and Communicate
Implement Document and Maintain
Appendix A Datasets
Appendix B Optimization and Sorting Measures
Appendix C More on Cross Validation
References
Index