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The lifecycle of a Machine Learning model is really complex. There are a number of phases starting from the exploration phase, which go up to deploying the model in production and then further maintaining it. Each lifecycle phase has its own set of hardware requirements and even information from one phase needs to flow to the other phases.
In this DataHour Anmol will be explaining MLOps from the start covering end-to-end operationalization of ML models using the power of Airflow and Kubernetes.
Prerequisites: Passion of learning Data Science and basic understanding of Machine Learning lifecycle phases and Kubernetes.
Anmol Krishan Sachdeva
Hybrid Cloud Architect at Google
Anmol Krishan Sachdeva, aka "greatdevaks", is an International Tech Speaker, a Distinguished Guest Lecturer, a Tech Panelist, and has represented India at several reputed International Hackathons. He is a Deep Learning Researcher and has about 8 publications in different domains.
He is an active conference organizer and previously has helped organize some of the most prestigious conferences like EuroPython, GeoPython & Python Machine Learning Conference, PyCon India, etc., and all of them were a huge success. He has done MSc in Advanced Computing (ML, AI, Robotics, Cloud Computing, Human Computer Interaction, and Computational Neuroscience) from University of Bristol, United Kingdom, and currently works at Google as a Hybrid Cloud Architect. In the past, Anmol has spoken at renowned conferences and tech forums like KubeCon, PyCon, EuroPython, GeoPython, and got invited as a Chief Guest / Guest of Honor at various events.
He likes innovating, keeping in touch with new technological trends, and mentoring people. Additionally, his interest lies in Cosmology and Neuroscience.
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