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Notes 

Google AI Blog: EfficientNet: Improving Accuracy and Efficiency through AutoML and Model Scaling

30 mai 2019 Francis

https://ai.googleblog.com/2019/05/efficientnet-improving-accuracy-and.html?m=1

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Keras: Feature extraction on large datasets with Deep Learning – PyImageSearch

27 mai 2019 Francis

https://www.pyimagesearch.com/2019/05/27/keras-feature-extraction-on-large-datasets-with-deep-learning/

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Enabling DevOps in A Hybrid Cloud Environment at DoD | Premier Developer

26 mai 2019 Francis

https://devblogs.microsoft.com/premier-developer/enabling-devops-in-a-hybrid-cloud-environment-at-dod/?_lrsc=d4ae705f-431b-4d86-9fa3-357c2fcaa700

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https://www.slideshare.net/mobile/lespetitescases/visite-guide-au-pays-de-la-donne-du-modle-conceptuel-au-modle-physique

24 mai 2019 Francis

https://www.slideshare.net/mobile/lespetitescases/visite-guide-au-pays-de-la-donne-du-modle-conceptuel-au-modle-physique

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Dcouvrabilit: mythes et ralit – SRENDIPIT

24 mai 2019 Francis

https://joseeplamondon.com/decouvrabilite-mythes-et-realite/

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Deploying a FaaS platform on OVH Managed Kubernetes using OpenFaaS – OVH Blog

24 mai 2019 Francis

https://www.ovh.com/fr/blog/deploying-a-faas-platform-on-ovh-managed-kubernetes-using-openfaas

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Google AI Blog: Moving Camera, Moving People: A Deep Learning Approach to Depth Prediction

24 mai 2019 Francis

https://ai.googleblog.com/2019/05/moving-camera-moving-people-deep.html?m=1

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Few-Shot Adversarial Learning of Realistic Neural Talking Head Models

23 mai 2019 Francis

https://youtu.be/p1b5aiTrGzY

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Neural-Symbolic Integration

23 mai 2019 Francis

http://www.neural-symbolic.org/

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What We Got Wrong: Lessons from the Birth of Microservices

20 mai 2019 Francis

https://www.infoq.com/presentations/google-lessons-microservices What We Got Wrong: Lessons from the Birth of Microservices Ben Sigelman talks about what Google got wrong about

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  • GitHub – jalammar/ecco: Visualize and explore NLP language models. Ecco creates interactive visualizations directly in Jupyter notebooks explaining the behavior of Transformer-based language models (like GPT2).
  • Data Science Infographic
  • SIRUS: Stable and Interpretable RUle Set
  • CLIP: Connecting Text and Images
  • Build Your own Recommendation Engine-Netflix Demystified: Demo+Code

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