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Introduction to Kubeflow Pipelines - Dan Anghel | ODSC Europe 2019

Dan Anghel is a Machine Learning Cloud Engineer working at Google for over 4 years. Prior to Google, Dan has spent more than 10 years in the French retail industry building scalable E-commerce solutions. Specialized in Machine Learning and Big Data, he is helping the largest Google customers build scalable production level solutions on Google Cloud Dan was speaking at ODSC Europe 2019 in London. → To watch more videos like this, visit https://learnai.odsc.com/ ← This tutorial will demonstrate how to use Kubeflow Pipelines to create a full Machine Learning application on Kubernetes. You will learn how to build and run a complete Machine Learning pipeline that does distributed training of a TensorFlow model. The trained model will further be deployed for serving predictions at scale and a Web frontend will be deployed to demonstrate requesting predictions from the trained model. In addition, participants will learn how to use a Jupyter notebook to build and run a Kubeflow pipeline using the Kubeflow Pipelines SDK. The cloud platform on which the Kubeflow Pipelines Machine Learning application will be deployed in this tutorial is Google Cloud Platform. Participants will thus become familiar with Google Cloud Platform tools such as Cloud Shell, Kubernetes Engine and Deployment Manager. Do You Like This Video? Share Your Thoughts in Comments Below Also, You can visit our website and choose the nearest ODSC Event to attend and experience all our Trainings and Workshops: https://odsc.com/europe/ Sign up for the newsletter to stay up to date with the latest trends in data science: https://opendatascience.com/newsletter/ Follow Us Online! • Facebook:   / opendatasci   • Instagram:   / odsc   • Blog: https://opendatascience.com/ • Linkedin:   / open-data-science   • Learning Videos: https://learnai.odsc.com #Kubeflow #MachineLearning #ODSC