A book about all that goes into building ML systems for production, but with a good focus on everything aside from building the actual model. This book was great, as it talks about all of the topics typically ignored or glossed over in most machine learning books: data engineering, data collection, deployment, model failures, tooling, and team structures.
Read as part of our weekly Data Science study group.
A book about all that goes into building ML systems for production, but with a good focus on everything aside from building the actual model. This book was great, as it talks about all of the topics typically ignored or glossed over in most machine learning books: data engineering, data collection, deployment, model failures, tooling, and team structures.
Read as part of our weekly Data Science study group.