This 2nd edition covers the entire data science life cycle, from data access and preparation to modeling, visualization and deployment.

George Mohler, a former professor of computer and information science at Indiana University-Purdue University Indianapolis who directed its Institute for Mathematical Modeling and Computational ...

However, as a consulting professional in the insurance industry, I have found that traditional MLOps often fall short in accelerating business results across the data science life cycle, as they ...

Although data science is interdisciplinary, one possible home for data science standards is in mathematics standards, as there are important mathematical tools and methods that support data science.