• Twitter
  RT @BethanyAllenEbr: When people go on TV and say that it is time to start sending planes over the Iranian homeland, I think, no, my Mar…
• GoogleCloudPlatform/cloudml-hypertune
  Metric Reporting Python Package for CloudML Hypertune
• jarokaz/mlops-labs
  This repo manages a set of labs designed to demonstrate best practices and patterns for implementing and operationalizing production grade ML workflows on Google Cloud Platform.

  With a few exceptions the labs are self-contained – they don’t rely on other labs. The goal is to create a portoflio of labs that can be utilized in development and delivery of scenario specific demos and workshops.

• Susan Floyd on Twitter: "What a find! “When A Woman Is Not Married: A Message from a Contented Spinster to Other Women Who Are Partly and Might Be Altogether as She Is,”an anonymous article published in Holland’s magazine, January 1918, Dallas, Texa
• Twitter
  RT @GeorgeMonbiot: In the midst of a climate emergency, our hills are being burnt – roasting wildlife and soil and releasing great plu…
• Twitter
  RT @itscaitlinhd: NEW: Negah Hekmati’s 5-year-old couldn’t sleep and asked her mom to stop speaking Farsi because she feared being se…
• Twitter
  RT @brandonshimoda: Iranians/Iranian-Americans have been detained/interrogated — some for 10+ hours — at the US-Canada border crossing…
• Laila Lalami on Twitter: "CBP detained more than 100 Iranians and Iranian-Americans at the border between Washington and Canada over the weekend. One woman was asked about the high school she graduated from 39 years ago. Another person was asked about his
• The Ultra-Wealthy Who Argue That They Should Be Paying Higher Taxes | The New Yorker
• Twitter
  RT @raejohnston: My heart broke so many times writing this.

  An estimated billion animals impacted by #AustralianBushfiresDisaster,…

• 10 ML & NLP Research Highlights of 2019
• Twitter
  RT @NASA_Marshall: On its 20th pass by Jupiter, @NASAJuno captured this close-up of the gas giant, with the luminous white clouds on t…
• Advances and Open Problems in Federated Learning
  Federated learning (FL) is a machine learning setting where many clients (e.g. mobile devices or
  whole organizations) collaboratively train a model under the orchestration of a central server (e.g. service
  provider), while keeping the training data decentralized. FL embodies the principles of focused data
  collection and minimization, and can mitigate many of the systemic privacy risks and costs resulting
  from traditional, centralized machine learning and data science approaches. Motivated by the explosive
  growth in FL research, this paper discusses recent advances and presents an extensive collection of open
  problems and challenges.

Digest powered by RSS Digest