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SUMMARY:Introduction to Deep-Learning
DESCRIPTION:Overview\nThe use of Deep Learning has seen a sharp increase of popularity and applicability over the last decade. While Deep Learning can be a useful tool for researchers from a wide range of domains\, taking the first steps in the world of Deep Learning can be somewhat intimidating. This introduction aims to cover the basics of Deep Learning in a practical and hands-on manner\, so that upon completion\, you will be able to train your first neural network and understand what next steps to take to improve the model. \nWe start with explaining the basic concepts of neural networks\, and then go through the different steps of a Deep Learning workflow. Learners will learn how to prepare data for deep learning\, how to implement a basic Deep Learning model in Python with Keras\, how to monitor and troubleshoot the training process and how to implement different layer types such as convolutional layers. \nAfter attending the workshop\, you should be able to: \n\nPrepare input data for use for deep learning\nDesign and train a Deep Neural Network\nTroubleshoot the learning process\nMeasure the performance of the network\nVisualise data and results\nRe-use existing network architectures with and without pre-trained weights\n\nPrerequisites\nParticipants are expected to have basic Python programming skills and familiarity with the Pandas package. Basic knowledge of statistics is also beneficial. \nPreliminary Agenda\nTuesday 22 February 2022 \n[ninja_tables id=”13063″] \nWednesday 23 February 2022 \n[ninja_tables id=”13064″] \nRegistration\nPlease register by following this link https://events.prace-ri.eu/event/1295/registrations/955/ \nFor questions regarding this event please contact us at training@enccs.se. \n————\nThis training is intended for users established in the European Union or a country associated to Horizon 2020.
URL:https://enccs.se/events/2022-02-introduction-to-deep-learning/
LOCATION:Online
CATEGORIES:ENCCS Event
ATTACH;FMTTYPE=image/jpeg:https://media.enccs.se/2021/11/Deep-learning-2-1.jpg
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