Developing a predictive app with open source & cloud Machine Learning APIs

PAPIs.io

Abstract: In this webinar targeted at developers who are new to Machine Learning, I’ll present the type of predictive features that can be integrated in any app (mobile, desktop, web…) and powered by data and machine learning. We’ll also look at what’s at stake when using ML in production and what the steps are to integrate this technology into real-world apps. In particular, we’ll review open source libraries and cloud platforms that make it easier to create and experiment with ML models, but also to deploy them to production. I’ll demo how to create a simple predictive model in Python with scikit-learn, how to deploy it as a REST API, and how to use that API.
About your host: Louis Dorard is General Chair of the PAPIs.io conferences, author of Boostrapping Machine Learning, and holds a PhD in ML from University College London. Louis is also the instructor of the <A TARGET="_blank" HREF="http://papis.io/workshops/operational-machine-learning" DATA-MSYS-CLICKTRACK="0" REL="nofollow noopener noreferrer">Operational Machine Learning workshop</A>.
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Developing a predictive app with open source & cloud Machine Learning APIs

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