The evolution from resource-constrained batch data mining to continuous MLOps at the cloud scale, and how to bring model development and DevOps together
MLOps Life Cycle for continuous training, integration, and deployment (CT/CI/CD) of models while building ML-assisted products.
Newsletter Issue 11: You define logic in traditional programs. Machine Learning extracts logic (models) from the data.
Newsletter Issue 8: Why machine learning and data science projects fail, and what you can do to void it.
Newsletter Issue 3: Arguments against and for embracing Agile in data science and machine learning projects.