Process

Survey of data science and machine learning lifecycle from resource-constrained batch data mining era to current MLOps era of CI/CD/CT at the cloud scale.

MLOps Lifecycle strings model and software development together in an unified machine learning life cycle for CI/CD/CT of ML products.

You define logic in traditional programs. Machine Learning extracts logic (models) from the data.

Why machine learning and data science projects fail, and what you can do to void it.

Arguments against and for embracing Agile in data science and machine learning projects.