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Prikvačeni tweet
How we built DeepMatch, a serverless event-driven ML service with a feature serving store
@SEEK_Geekhttps://medium.com/seek-blog/serverless-machine-learning-inference-with-tika-and-tensorflow-fb578af0eaba …Hvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
The first deep-learning project on
@github uses Argo CD for data acquisition, training and inference pipelines@argoprojhttps://github.blog/2020-01-22-how-we-built-good-first-issues/ …Hvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
A 17x decrease in BERT inference latency on CPU (3x on GPU) makes the ONNX runtime worth looking intohttps://cloudblogs.microsoft.com/opensource/2020/01/21/microsoft-onnx-open-source-optimizations-transformer-inference-gpu-cpu/ …
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ECS in the enterprise begets a PaaS or at least some tooling. But unlike Kubernetes, I haven't heard as much about ECS platforms. Empire is an open-source PaaS built on ECS & supports a subset of the Heroku API. Probably not the first or last ECS PaaS.https://github.com/remind101/empire …
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The Kafka dev experience wasn't fun in
@YelpEngineering's first approach to Kafka as a service. So they built out a new producer abstraction, sidecar, relay and discovery service. Flink is used on the consumer side. Good to hear these stories
https://engineeringblog.yelp.com/2020/01/streams-and-monk-how-yelp-approaches-kafka-in-2020.html …pic.twitter.com/evrpHT555c
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Sometimes knowing the confidence of a prediction is as important, or more, than being accurate. Hard tho if it's an inverse relationship!https://ai.googleblog.com/2020/01/can-you-trust-your-models-uncertainty.html …
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"The most challenging thing is acquiring patience about how ML-based data products are adopted in the company."
https://twitter.com/vukosi/status/1172412169125711874 …
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> I used to be all about “the best language for the problem.” Now I recommend “the language your team knows best, as long as it’s good enough.”https://twitter.com/jessitron/status/1220169897973440512 …
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I'm wondering what the workflow is when you start with interactive development in JupyterHub. Once you've imported dagstermill, can you still run the notebook interactively in JupyterHub? Or must you use dagit?
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Papermill allows you to parameterize Jupyter notebooks and execute them. Dagstermill builds on this by integrating notebooks as a step in a data pipeline.
Inputs, outputs are handled by dagster.
Logs and the notebook as executed is stored by dagit.
https://dagster.readthedocs.io/en/0.6.7.post0/sections/learn/guides/data_science/data_science.html …Prikaži ovu nitHvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
Nice summary by
@krisabdelmessih on p values, from Statistics Done Wrong https://moontowermeta.com/notes-on-statistics-done-wrong/ …pic.twitter.com/AqOaDj25lT
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This is pretty significant for privacy. A corpus of 3 billion photos (with names?) so presumably they have Facebook photo data. It's hard but legal to scrape LinkedIn. Twitter too I assume.https://twitter.com/kashhill/status/1218510902556811264 …
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The Rust ecosystem is more of a house of cards than I thought (although still better than some other languages)https://medium.com/@shnatsel/smoke-testing-rust-http-clients-b8f2ee5db4e6 …
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Really enjoyed this about WePay's data infra evolution. It's a comprehensive blueprint of problems and solutions at each stage from direct prod database access -> self-serve.https://twitter.com/criccomini/status/1202666715596722177 …
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"How to build a PaaS for 1500 engineers" by
@srVaroa * main value-add: integration * don't compete with commercial companies * when components change users shouldn't notice * small automations at scale add up * north star: successful deployments per week https://srvaroa.github.io/paas/infrastructure/platform/kubernetes/cloud/2020/01/02/talk-how-to-build-a-paas-for-1500-engineers.html …Hvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
ING WBBA team's Data Analytics Platform. Notable for: * mostly open-source components * access only via remote desktop * k8s running both interactive & batch workloads (via multi-project quotas + pod priority & pre-emption) * Amundsen + Apache Atlashttps://www.youtube.com/watch?v=8cE9ppbnDPs …
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I've created and used overly granular and constraining types before. Knowing when not to is hard.https://twitter.com/BrandonBloom/status/1211575651892744192 …
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A privacy-preserving search engine to compete with Google, using query logs for the *main index* and GBDT for ranking
@cliqz have open-sourced
* Keyvi, an FST-based key-value store for approximate matching
* Granne, graph-based ANN searchhttps://0x65.dev/blog/2019-12-06/building-a-search-engine-from-scratch.html …Hvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
I wonder at what scale focusing on utilization makes the most sense.
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Alibaba moved from multiple clusters to a centralised k8s cluster to maximise utilization. Combining online and office workloads they can get up to 40% CPU utilization. They've a cluster running 10k nodes, which is a big blast radius.https://www.infoq.com/presentations/alibaba-kubernetes …
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A great overview of CUE (aka cuelang).
@cedricgc compares it to other config tools, describes what makes it unique, and explains how it tackles the challenge of configuration at scale https://blog.cedriccharly.com/post/20191109-the-configuration-complexity-curse/ …Hvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi
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on the "Future of Data Engineering" is up! I cover the six stages of data pipeline maturity:
0. None
1. Batch
2. Realtime
3. Integration
4. Automation
5. Decentralization
Check it out!
(I'm so sorry for the link picture)