Practical applications of machine learning involves building systems that optimizes one or more objectives. For any solution of moderate complexity, we get confronted with finding optimal tradeoffs between different objectives such as accuracy vs cost, relevance vs revenue, ads vs content etc.

In this DataHour, Rahul will explain a formal setup to pose the problem of multiple objectives mathematically and solve them through python based optimisers.

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