Referring Tweets

@DataScienceNIG
@DataScienceNIG Here comes an exciting times with @TensorFlow library for learning to rank! TF-Ranking provides a framework to evaluate and choose different ranking models + empowering users to develop their own custom models. Paper: t.co/KoRo84pXZY GitHub: t.co/wP9a5KIKEV t.co/6fwrDOQkLJ
@lc0d3r
@lc0d3r Great new release by @TensorFlow TensorFlow Ranking - t.co/groHuQnYQH It's definitely very valuable to have a good framework, especially not only for point-wise ranking, but also pair and list-wise #DeepLearning #ranking - t.co/nwacBDBa4F t.co/YE02Z5k3Yz
@DynamicWebPaige
@DynamicWebPaige 31) TF-Ranking A @TensorFlow library focused on ordering lists of items to maximize list utility. Supports pairwise or listwise loss functions, multi-item scoring, ranking metric optimization, and unbiased learning-to-rank! 👩‍💻 t.co/UkKDbGBN0C 📊 t.co/IMNj8zpE5U
@sjoerdapp
@sjoerdapp 🤖🤖🤖 tensorflow/ranking by @tensorflow via @GitHub t.co/acotxTiISR #ai #emergingtech #machinelearning
@ghb_hq
@ghb_hq 'ranking' by tensorflow : Learning to Rank in TensorFlow t.co/WTFcrY3pVo #dev #programming #tech #python
@DrAliMonam
@DrAliMonam tensorflow/ranking t.co/o0CX2ECdUs #MachineLearning #ai #emergingtech t.co/GXiwsE8mw3
@PhillyTalentAI
@PhillyTalentAI Google has released TF-Ranking library for learning-to-rank. "The objective of learning-to-rank algorithms is minimizing a loss function defined over a list of items to optimize the utility of the list ordering for any given application." #LAN2018 #toolai t.co/QEJnyLZtrM t.co/IgyL0M2ktg
@kdubovikov
@kdubovikov Learning to rank with TensorFlow: t.co/lpZ5hY0Upn ps it requires Bazel :(
@isaac_burbank
@isaac_burbank #TensorFlow now has a library for Learning-to-Rank. t.co/GRHLfrDOgz t.co/h1kRMNvmkA

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お知らせ

  • 2021/12/31: デザインを刷新しました
  • 2021/04/08: 日本語Kaggleのカテゴリを新設しました