Building Machine Learning Web Applications
October 1st, 2020
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Data Science combines human domain knowledge and intuition with programmatic data analysis to find valuable patterns that provide business value. Once relevant dynamics have been identified, these techniques should be automated so that continuous insights can be provided effortlessly to decision makers that rely on this information. Often Data Science content only shows methods to analyze data, but in this post you will also learn, at a high-level, how to operationalize Data Science for Smart Automation.
People who build Machine Learning (ML) and Operations Research (OR) models often think of their models as single entities that act in isolation, and they don't realize how multiple models can be combined to produce complex real-time predictions that can dynamically adjust based on how much time a request can be delayed. In this course, we show you how to implement a smart streaming system that uses the Pub/Sub pattern to dynamically plug-in models in while running in production without affecting on-going requests.