Dec 20, 2022Security and Privacy in ML-Enabled SystemsThis post covers content from the “security and privacy” lecture of our Machine Learning in Production course. For other chapters see the table of content. Malicious actors may try to interfere with any software system and there is a long history of attempts, on one side, to secure software systems…Security42 min readSecurity42 min read
Nov 17, 2022Integration and System TestingThis post covers some content from the “Infrastructure Quality” lectures of our Machine Learning in Production course. For other chapters see the table of content. As discussed throughout this book, machine learning contributes components to a software product. While we can test machine-learned models in isolation, can test individual steps…Se4ml10 min readSe4ml10 min read
Nov 14, 2022Quality Assurance for Machine-Learning PipelinesThis post covers some content from the “Infrastructure Quality” lectures of our Machine Learning in Production course. For other chapters see the table of content. Machine-learning pipelines contain the code to train, evaluate, and deploy models that are then used within products. As with all code, the code in a…Se4ml23 min readSe4ml23 min read
Nov 3, 2022Quality Assurance BasicsThis post covers some content from the “Infrastructure Quality” lectures of our Machine Learning in Production course. For other chapters see the table of content. Quality assurance broadly refers to all activities that evaluate whether a (software) system meets the quality requirements. Typical activities include testing and code reviews, but…Se4ml19 min readSe4ml19 min read
Oct 27, 2022Safety in ML-Enabled SystemsTogether with parts of “Planning for Mistakes,” this post covers the lecture “Safety” of our Machine Learning in Production course. For other chapters see the table of content. Safety is the prevention of a system failure or malfunction that results in (1) death or serious injury, (2) loss or severe…Se4ml23 min readSe4ml23 min read
Sep 13, 2022Planning for Machine-Learning MistakesThis post covers some content from the “Requirements and Risk” lectures of our Machine Learning in Production course. For other chapters see the table of content. Predictions from machine-learned models in a software system may be wrong. Depending on the system design, wrong predictions can cause the system to display…Se4ml30 min readSe4ml30 min read
Sep 12, 2022Gathering Requirements for ML -Enabled SystemsThis post covers some content from the “Requirements and Risk” lectures of our Machine Learning in Production course. For other chapters see the table of content. Much of software engineering is focused generally on simply getting engineers to think and plan a little before diving into coding, as to avoid…Se4ml28 min readSe4ml28 min read
Sep 2, 2022Setting and Measuring Goals for Machine Learning ProjectsThis post covers some content from the “Goals and Success Measures” lectures of our Machine Learning in Production course. For other chapters see the table of content. With a strong emphasis on machine learning, many projects focus on optimizing ML models for accuracy. However, when building production systems, the machine…Se4ml22 min readSe4ml22 min read
Sep 1, 2022When to use Machine LearningThis post covers some content from the “Goals and Success Measures” lectures of our Machine Learning in Production course. For other chapters see the table of content. Machine learning is now commonly used in software products of all kinds. Not in all cases, machine learning is appropriate. In some cases…Se4ml11 min readSe4ml11 min read
Jul 11, 2022Fairness in Machine Learning and ML-Enabled ProductsThis post covers content from the “Fairness” lectures of our Machine Learning in Production course. For other chapters see the table of content. Fairness is one of the most discussed topics in machine learning, coming from realizations how models trained with data could pick up on biases in that data…Responsible Ai58 min readResponsible Ai58 min read
