Executive Briefing: A new taxonomy of machine learning Session details
Rachel Silver shares a new taxonomy of machine learning approaches that distinguishes between those that are providing enormous competitive advantage and those that represent merely small, incremental improvements on existing analytical tools and details a framework for evaluating ML approaches on several dimensions of complexity, including: The amount of data required (such as for training) The computational complexity of the training algorithm Real-time streaming requirements (versus just batch computing) Data throughput for the deployed model to process Rachel explores examples of how to apply this framework to real-world machine learning approaches and highlights the technical requirements of supporting the most disruptive examples of ML solutions.
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AuthorRachel Silver is a Principal Technical Product Manager Archives
November 2023
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