"backprop" meaning in All languages combined

{
  "etymology_text": "Shortening of backpropagation.",
  "head_templates": [
    {
      "args": {
        "1": "-"
      },
      "expansion": "backprop (uncountable)",
      "name": "en-noun"
    }
  ],
  "lang": "English",
  "lang_code": "en",
  "pos": "noun",
  "senses": [
    {
      "categories": [
        {
          "kind": "other",
          "name": "English entries with incorrect language header",
          "parents": [
            "Entries with incorrect language header",
            "Entry maintenance"
          ],
          "source": "w"
        },
        {
          "kind": "other",
          "name": "Pages with 1 entry",
          "parents": [],
          "source": "w"
        },
        {
          "kind": "other",
          "name": "Pages with entries",
          "parents": [],
          "source": "w"
        }
      ],
      "examples": [
        {
          "ref": "2015, Sanjeev Arora, Yingyu Liang, Tengyu Ma, “Why are deep nets reversible: A simple theory, with implications for training”, in arXiv:",
          "text": "The generative model suggests a simple modification for training---use an input to produce several synthetic inputs with the same label, and include them in the backprop training.",
          "type": "quote"
        },
        {
          "ref": "2020, Timothy P. Lillicrap, Adam Santoro, Luke Marris, Colin J. Akerman, Geoffrey Hinton, “Backpropagation and the brain”, in Nature:",
          "text": "In machine learning, backpropagation of error (‘backprop’) is the algorithm most often used to train deep neural networks and is the most successful learning procedure for these networks.",
          "type": "quote"
        }
      ],
      "glosses": [
        "backpropagation"
      ],
      "id": "en-backprop-en-noun-K9Bj4-wG",
      "links": [
        [
          "backpropagation",
          "backpropagation"
        ]
      ],
      "tags": [
        "uncountable"
      ]
    }
  ],
  "word": "backprop"
}

{
  "etymology_text": "Shortening of backpropagation.",
  "head_templates": [
    {
      "args": {
        "1": "-"
      },
      "expansion": "backprop (uncountable)",
      "name": "en-noun"
    }
  ],
  "lang": "English",
  "lang_code": "en",
  "pos": "noun",
  "senses": [
    {
      "categories": [
        "English entries with incorrect language header",
        "English lemmas",
        "English nouns",
        "English terms with quotations",
        "English uncountable nouns",
        "Pages with 1 entry",
        "Pages with entries"
      ],
      "examples": [
        {
          "ref": "2015, Sanjeev Arora, Yingyu Liang, Tengyu Ma, “Why are deep nets reversible: A simple theory, with implications for training”, in arXiv:",
          "text": "The generative model suggests a simple modification for training---use an input to produce several synthetic inputs with the same label, and include them in the backprop training.",
          "type": "quote"
        },
        {
          "ref": "2020, Timothy P. Lillicrap, Adam Santoro, Luke Marris, Colin J. Akerman, Geoffrey Hinton, “Backpropagation and the brain”, in Nature:",
          "text": "In machine learning, backpropagation of error (‘backprop’) is the algorithm most often used to train deep neural networks and is the most successful learning procedure for these networks.",
          "type": "quote"
        }
      ],
      "glosses": [
        "backpropagation"
      ],
      "links": [
        [
          "backpropagation",
          "backpropagation"
        ]
      ],
      "tags": [
        "uncountable"
      ]
    }
  ],
  "word": "backprop"
}