Row 5271

Row ID: 5271 | Dataset Entry | Axioma AXP Content Repository

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TL;DR: Uber follows a 2 layer approach. They use traditional graph algorithms like Dijkstra followed by learned embeddings and a lightweight self-attention neural network to reliably predict estimated time of arrival or ETA.

[How Uber uses ML to ETAs](https://open.substack.com/pub/codecompass00/p/uber-billion-dollar-problem-predicting-eta?r=rcorn&utm_campaign=post&utm_medium=web)

https://preview.redd.it/cg6r82se67xc1.png?width=1358&format=png&auto=webp&s=4ac9e946b30d858721b842f0f4407dfa6c50ce3e

FieldValue
text TL;DR: Uber follows a 2 layer approach. They use traditional graph algorithms like Dijkstra followed by learned embeddings and a lightweight self-attention neural network to reliably predict estimated time of arrival or ETA. [How Uber uses ML to ETAs](https://open.substack.com/pub/codecompass00/p/uber-billion-dollar-problem-predicting-eta?r=rcorn&utm_campaign=post&utm_medium=web) https://preview.redd.it/cg6r82se67xc1.png?width=1358&format=png&auto=webp&s=4ac9e946b30d858721b842f0f4407dfa6c50ce3…
label r/deeplearning
dataType post
communityName r/deeplearning
datetime 2024-04-28
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Raw Record

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  "text": "TL;DR: Uber follows a 2 layer approach. They use traditional graph algorithms like Dijkstra followed by learned embeddings and a lightweight self-attention neural network to reliably predict estimated time of arrival or ETA.\n\n[How Uber uses ML to ETAs](https://open.substack.com/pub/codecompass00/p/uber-billion-dollar-problem-predicting-eta?r=rcorn&utm_campaign=post&utm_medium=web)\n\nhttps://preview.redd.it/cg6r82se67xc1.png?width=1358&format=png&auto=webp&s=4ac9e946b30d858721b842f0f4407dfa6c50ce3e\n\n",
  "label": "r/deeplearning",
  "dataType": "post",
  "communityName": "r/deeplearning",
  "datetime": "2024-04-28",
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