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ai guide Reading Stanford CS230

AI Project Strategy: Three Hours in a Spreadsheet Buys Back Weeks

Andrew Ng demonstrates error analysis on a deep researcher: columns are the pipeline stages, rows are 10 to 100 queries, you only look at the ones that went badly, and you mark each cell where something broke. The percentages don't have to sum to 100%. He says it takes three or four hours and saves weeks of going the wrong direction — and the fraction of people who actually do it is far below 100%.

#error-analysis#ai-agent#evaluation#machine-learning#stanford-cs230
ai guide Reading Stanford CS230

Full Cycle of a DL Project: You Get Two Days to Collect Data

Andrew Ng walks a face-recognition door system through the entire project lifecycle, and the whole lecture has one thesis: speed. He gives teams a two-day deadline, on the reasoning that 'time spent preparing data should be commensurate with the time it takes to train the model once.' It closes on a line: my job is to build something that actually works, and that is not the same as building something that works on the test set.

#machine-learning#data-centric-ai#mlops#error-analysis#stanford-cs230