Catégorie : Notes
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How to Gain State-Of-The-Art Result on Tabular Data with Deep Learning and Embedding Layers
https://towardsdatascience.com/how-to-gain-state-of-the-art-result-on-tabular-data-with-deep-learning-and-embedding-layers-d1eb6b83c52c
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Security | Open Distro
https://opendistro.github.io/for-elasticsearch/features/security.html?&trk=psm_a131L0000057UoHQAU&trkCampaign=pac_q3_07-19_opendistro_ps_security&sc_channel=psm&sc_campaign=PAC-PaaS-Open-Distro-for-Elasticsearch-2019-Austin&sc_publisher=FB&sc_category=Analytics&sc_country=namer&sc_geo=NAMER&sc_outcome=paas_digital_marketing&sc_detail=1200×628&sc_content=Interest_JobTitles&sc_segment=security&sc_medium=PAC-PaaS-P%7CFB%7CSocial-P%7CAll%7CAW%7CAnalytics%7CElasticsearch+Service%7CNAMER%7CEN%7CSponsored+Content%7Cxx%7COpen+Distro+for+Elasticsearch
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AWS launches SageMaker Studio, a web-based IDE for machine learning
https://techcrunch.com/2019/12/03/aws-launches-sagemaker-studio-a-web-based-ide-for-machine-learning/?fbclid=IwAR15l0sHI0dvpxBZMjL6Xn6hz5rswm_fB2MIc3is423kETXoVyU8lCmRFEw AWS launches SageMaker Studio, a web-based IDE for machine learning – TechCrunch At its re:Invent conference, AWS CEO Andy Jassy today announced the launch of SageMaker Studio, a web-based IDE for building and training machine learning workflows. It includes everything a data scientist would need to get started, including ways to organize notebooks, data…
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Metaflow
https://metaflow.org/
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Adoption of Cloud-Native Architecture, Part 1: Architecture Evolution and Maturity
https://www.infoq.com/articles/cloud-native-architecture-adoption-part1/?utm_campaign=infoq_content&utm_source=infoq&utm_medium=feed&utm_term=Microservices
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CamemBERT
https://camembert-model.fr/ Cliquer pour accéder à 1911.03894.pdf CamemBERT CamemBERT. CamemBERT is a state-of-the-art language model for French based on the RoBERTa architecture pretrained on the French subcorpus of the newly available multilingual corpus OSCAR.. We evaluate CamemBERT in four different downstream tasks for French: part-of-speech (POS) tagging, dependency parsing, named entity recognition (NER) and natural language…
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1911.11423 Single Headed Attention RNN: Stop Thinking With Your Head
https://arxiv.org/abs/1911.11423
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The Phoenicorn Project – DevOps.com
https://devops-com.cdn.ampproject.org/c/s/devops.com/the-phoenicorn-project/amp/
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Google tackles the black box problem with Explainable AI – BBC News
https://www-bbc-com.cdn.ampproject.org/c/s/www.bbc.com/news/amp/technology-50506431
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The Reinforcement-Learning Methods that Allow AlphaStar to Outcompete Almost All Human Players at StarCraft II
https://www.kdnuggets.com/2019/11/reinforcement-learning-methods-alphastar-outcompete-human-players-starcraft.html
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Kubernetes-based event-driven autoscaling (KEDA)
https://cloudblogs.microsoft.com/opensource/2019/11/19/keda-1-0-release-kubernetes-based-event-driven-autoscaling/
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Monitor Azure Red Hat OpenShift Kubernetes clusters with Azure Monitor for containers | Azure updates | Microsoft Azure
https://azure.microsoft.com/en-us/updates/monitor-azure-red-hat-openshift-kubernetes-clusters-with-azure-monitor-for-containers/
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MLQA: Evaluating cross-lingual extractive question answering
https://ai.facebook.com/blog/mlqa-evaluating-cross-lingual-extractive-question-answering?__xts__%5B0%5D=68.ARAPmZIKpXDv733JFeRrrPTwAW7sPI8x6Rr5cnjswy_qpHRknmFeFqbPhMZWyvk7HIV34d_pGh5PE-3Zg-gdlRDd8JWGueS1uvb75i0o4sQ3WvT4N0MklDhpy2_XSrleOGSzBkhyjw6QuYlEDztm4SvIQR8CMfMfnfmO3aF8iIBo0WgIcTMTE-CPpTQZQRiNdLsV362f2AVkzYGMW82j1nbSA5Xd-oi8XJ86MPEk1fFYcL44k8-NwH0R44cKFOKS6JyNn1316LQ8w2_BJC7QiI2E73tkbLXVepU3&__tn__=K%2AF MLQA: Evaluating cross-lingual extractive question answering Facebook AI is sharing MLQA, an extractive question answering (QA) evaluation benchmark aligned across Arabic, German, Hindi, Spanish, Vietnamese, and Simplified Chinese. It will help the AI community improve and extend QA in more languages. ai.facebook.com
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Continuous delivery for machine learning
https://www.thoughtworks.com/insights/articles/intelligent-enterprise-series-cd4ml?fbclid=IwAR2Sxz4GlfNiI22wSKUiFoRi7AkJVK1VJVfeiB06zeM2ZrCz1IiZmN4DxLM
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ASP.NET Blog | gRPC vs HTTP APIs
https://devblogs.microsoft.com/aspnet/grpc-vs-http-apis/
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https://www.zdnet.com/google-amp/article/facebooks-latest-giant-language-ai-hits-computing-wall-at-500-nvidia-gpus/
https://www.zdnet.com/google-amp/article/facebooks-latest-giant-language-ai-hits-computing-wall-at-500-nvidia-gpus/
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Everything you need to know about Regular Expressions
https://towardsdatascience.com/everything-you-need-to-know-about-regular-expressions-8f622fe10b03
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GitHub – NVIDIAGameWorks/kaolin: A PyTorch Library for Accelerating 3D Deep Learning Research
https://github.com/NVIDIAGameWorks/kaolin
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Activation maps for deep learning models in a few lines of code
https://towardsdatascience.com/activation-maps-for-deep-learning-models-in-a-few-lines-of-code-ed9ced1e8d21
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GitHub – modin-project/modin: Modin: Speed up your Pandas workflows by changing a single line of code
https://github.com/modin-project/modin
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https://www.researchgate.net/publication/322617800_New_Deep_Learning_Algorithms_beyond_Backpropagation_IBM_Developers_UnConference_2018_Zurich
https://www.researchgate.net/publication/322617800_New_Deep_Learning_Algorithms_beyond_Backpropagation_IBM_Developers_UnConference_2018_Zurich
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Understanding kubernetes networking: pods – Google Cloud Platform – Community – Medium
https://medium.com/google-cloud/understanding-kubernetes-networking-pods-7117dd28727
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Google AI Blog: Introducing the Next Generation of On-Device Vision Models: MobileNetV3 and MobileNetEdgeTPU
https://ai.googleblog.com/2019/11/introducing-next-generation-on-device.html?m=1
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Five Microservices Worst Practices
https://devops-com.cdn.ampproject.org/c/s/devops.com/five-microservices-worst-practices/amp/
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Kubernetes production best practices
https://learnk8s.io/production-best-practices/
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Restful Versioning | Peter Ritchie
http://blog.peterritchie.com/RESTful-Versioning/
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Polynote | The polyglot Scala notebook
https://polynote.org/ https://github.com/polynote/polynote
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Pretrained Model Weights (Pytorch) | Kaggle
https://www.kaggle.com/abhishek/pretrained-model-weights-pytorch
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Linear Algebra and Probability Theory Review for ML
https://towardsdatascience.com/linear-algebra-and-probability-theory-review-for-ml-e3d2d70c5eb3 Linear Algebra and Probability Theory Review for ML Probability theory is our way of dealing with uncertainty in the world, It’s the mathematical framework that estimates the probability of an event happening with respect to other possible events… towardsdatascience.com
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GPT2 Pretrained Models (Pytorch) | Kaggle
https://www.kaggle.com/abhishek/gpt2-pytorch
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GPT2 Output Dataset | Kaggle
https://www.kaggle.com/abhishek/gpt2-output-data
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State of DevOps 2019 : Ce qu’il faut retenir
https://www.slideshare.net/mobile/adlenesifi/state-of-devops-2019-ce-quil-faut-retenir
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Dodecadialogue
https://parl.ai/projects/dodecadialogue/
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Kubernetes Scheduler 101 – Cloud Native Computing Foundation
https://www.cncf.io/blog/2019/11/11/kubernetes-scheduler-101/
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GitHub – deezer/spleeter: Deezer source separation library including pretrained models.
https://github.com/deezer/spleeter
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Deployment Strategies Defined | Itay as a Service
http://blog.itaysk.com/2017/11/20/deployment-strategies-defined
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Azure Synapse Analytics
https://azure.microsoft.com/en-us/blog/azure-sql-data-warehouse-is-now-azure-synapse-analytics/
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Expanding the Azure Stack portfolio to run hybrid applications across the cloud, datacenters, and the edge | Blog | Microsoft Azure
https://azure.microsoft.com/en-us/blog/expanding-the-azure-stack-portfolio-to-run-hybrid-applications-across-the-cloud-datacenter-and-the-edge/
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OpenAI GPT-2 dataset. 1.5 billions hyperparameters
https://github.com/openai/gpt-2-output-dataset
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Keras Tuner
https://keras-team.github.io/keras-tuner/
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1910.12279 Memeify: A Large-Scale Meme Generation System
https://arxiv.org/abs/1910.12279
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Re-imagining developer productivity with AI-assisted tools | Visual Studio Blog
https://devblogs.microsoft.com/visualstudio/ai-assisted-developer-tools/
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Colorizing Pokemon with Deep Learning – Hackerstreak
https://hackerstreak.com/colorizing-pokemon-with-deep-learning/
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Facebook’s SlowFast video classifier AI was inspired by primate eyes | VentureBeat
https://venturebeat.com/2019/11/04/facebooks-slowfast-video-classifier-ai-was-inspired-by-primate-eyes/?fbclid=IwAR35qEw7h_wctr2p_Rik_l2uF-9YtToRqr_NBnzSD7jDDqjYtns-1q2-G6Q
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40 Techniques Used by Data Scientists – Data Science Central
https://www.datasciencecentral.com/profiles/blogs/40-techniques-used-by-data-scientists?imm_mid=0f1a15&cmp=em-data-na-na-newsltr_20170517
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Kubernetes Concepts and Deployment E-book | Microsoft Azure
https://azure.microsoft.com/en-us/resources/kubernetes-up-and-running/
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History’s message about regulating AI
https://www.brookings.edu/research/historys-message-about-regulating-ai/
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Kubernetes Concepts and Deployment E-book | Microsoft Azure
https://azure.microsoft.com/en-us/resources/kubernetes-up-and-running/