On site01The Growing Role of MLOps: Where Data Science Meets DevOps
Why deploying and maintaining machine-learning models requires the shared practices of data science and DevOps.
- MLOps
- DevOps
- Machine Learning
ARCHIVE // 02
Practical notes on AI engineering, data, and software systems. Every article is available here in the archive.
Writing index
On site01Why deploying and maintaining machine-learning models requires the shared practices of data science and DevOps.
On site02A practical tour of sales, customers, inventory, marketing, recommendations, fraud, and supply-chain analytics.
On site03A practical introduction to descriptive statistics, probability, inference, regression, and Bayesian reasoning with Python examples.
On site04The technical work, collaboration, reporting, and communication that shape a data scientist’s working day.
On site05A guide to statistical, predictive, forward-fill, and backward-fill approaches for handling missing observations.