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The Missing Step in Moving from Data to Models: Feature Engineering for Machine Learning
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| por Amanda Casari Seguir 0 Seguidores em 06 ago 2018 |
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48:10

Resumo
Machine learning fits mathematical models to data to derive insights or make predictions. In this talk, we will dive deeper into the mechanisms behind popular feature engineering techniques and walk through use cases of where these techniques are most useful. You will be able to better identify which methods to use based on your data and the problem you are working to solve.

Minibiografia

Amanda Casari is a senior product manager and data scientist for Concur Labs, where she designs prototypes, interfaces and future tech for travel and expense. She is a frequent speaker and works to foster an inclusive Seattle data community, volunteering with groups like PyLadies and NASA Datanauts. Before joining SAP Concur, Amanda worked as data scientist and engineer.

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