Machine learning offers a fantastically powerful toolkit for building useful complexprediction systems quickly. This paper argues it is dangerous to think ofthese quick wins as coming for free. Using the software engineering frameworkof technical debt, we find it is common to incur massive ongoing maintenancecosts in real-world ML systems. We explore several ML-specific risk factors toaccount for in system design. These include boundary erosion, entanglement,hidden feedback loops, undeclared consumers, data dependencies, configurationissues, changes in the external world, and a variety of system-level anti-patterns.

In statistical hypothesis testing, a result has statistical significance when it is very unlikely to have occurred given the null hypothesis.

In computer science, a B-tree is a self-balancing tree data structure that maintains sorted data and allows searches, sequential access, insertions, and deletions in logarithmic time. The B-tree generalizes the binary search tree, allowing for nodes with more than two children.[2] Unlike other self-balancing binary search trees, the B-tree is well suited for storage systems that read and write relatively large blocks of data, such as discs. It is commonly used in databases and file systems.

Peter Naur (25 October 1928 – 3 January 2016)[1] was a Danish computer science pioneer and Turing award winner. He is best known as a contributor, with John Backus, to the Backus–Naur form (BNF) notation used in describing the syntax for most programming languages. He also contributed to creating the language ALGOL 60.

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