{
  "id": 328314,
  "title": "H&M recommender system demo with Streamlit",
  "url": "/competitions/h-and-m-personalized-fashion-recommendations/discussion/328314",
  "author_name": "Mohammed Obeidat",
  "post_date": "2022-05-31T20:52:32.543000",
  "votes": 2,
  "comment_count": 0,
  "views": 0,
  "content": "<p><a href=\"https://share.streamlit.io/mnobeidat13/handm-recommender-system/main\" target=\"_blank\">https://share.streamlit.io/mnobeidat13/handm-recommender-system/main</a><br>\n<a href=\"https://github.com/mnobeidat13/HandM\" target=\"_blank\">https://github.com/mnobeidat13/HandM</a></p>\n<p>Follow the link to see a demo of my work on data in this competition.<br>\nI built 5 different recommendation models using:<br>\nImage Embeddings<br>\nText Emebeddings<br>\nFeatures Embeddings<br>\nTFRS model Embeddings<br>\nand a combination of all embeddings.</p>\n<p>The GUI is built with streamlit.io and the app is hosted on their cloud.<br>\nIn documentation section you can find all notebooks used in the project or head over to my profile.<br>\nGive upvotes if find it interesting.</p>\n<p>I used <a href=\"https://www.kaggle.com/viji1609\" target=\"_blank\">@viji1609</a> TFRS model which you can find here. <a href=\"https://www.kaggle.com/code/viji1609/h-m-basic-retrieval-model-tf-recommender\" target=\"_blank\">https://www.kaggle.com/code/viji1609/h-m-basic-retrieval-model-tf-recommender</a></p>",
  "messages": [
    {
      "id": 1807230,
      "postDate": "2022-05-31T20:52:32.543Z",
      "content": "<p><a href=\"https://share.streamlit.io/mnobeidat13/handm-recommender-system/main\" target=\"_blank\">https://share.streamlit.io/mnobeidat13/handm-recommender-system/main</a><br>\n<a href=\"https://github.com/mnobeidat13/HandM\" target=\"_blank\">https://github.com/mnobeidat13/HandM</a></p>\n<p>Follow the link to see a demo of my work on data in this competition.<br>\nI built 5 different recommendation models using:<br>\nImage Embeddings<br>\nText Emebeddings<br>\nFeatures Embeddings<br>\nTFRS model Embeddings<br>\nand a combination of all embeddings.</p>\n<p>The GUI is built with streamlit.io and the app is hosted on their cloud.<br>\nIn documentation section you can find all notebooks used in the project or head over to my profile.<br>\nGive upvotes if find it interesting.</p>\n<p>I used <a href=\"https://www.kaggle.com/viji1609\" target=\"_blank\">@viji1609</a> TFRS model which you can find here. <a href=\"https://www.kaggle.com/code/viji1609/h-m-basic-retrieval-model-tf-recommender\" target=\"_blank\">https://www.kaggle.com/code/viji1609/h-m-basic-retrieval-model-tf-recommender</a></p>",
      "rawMarkdown": "https://share.streamlit.io/mnobeidat13/handm-recommender-system/main\nhttps://github.com/mnobeidat13/HandM\n\nFollow the link to see a demo of my work on data in this competition.\nI built 5 different recommendation models using:\nImage Embeddings\nText Emebeddings\nFeatures Embeddings\nTFRS model Embeddings\nand a combination of all embeddings.\n\nThe GUI is built with streamlit.io and the app is hosted on their cloud.\nIn documentation section you can find all notebooks used in the project or head over to my profile.\nGive upvotes if find it interesting.\n\nI used @viji1609 TFRS model which you can find here. https://www.kaggle.com/code/viji1609/h-m-basic-retrieval-model-tf-recommender",
      "votes": 2
    }
  ],
  "comments": [],
  "raw_markdown_by_id": {
    "1807230": "https://share.streamlit.io/mnobeidat13/handm-recommender-system/main\nhttps://github.com/mnobeidat13/HandM\n\nFollow the link to see a demo of my work on data in this competition.\nI built 5 different recommendation models using:\nImage Embeddings\nText Emebeddings\nFeatures Embeddings\nTFRS model Embeddings\nand a combination of all embeddings.\n\nThe GUI is built with streamlit.io and the app is hosted on their cloud.\nIn documentation section you can find all notebooks used in the project or head over to my profile.\nGive upvotes if find it interesting.\n\nI used @viji1609 TFRS model which you can find here. https://www.kaggle.com/code/viji1609/h-m-basic-retrieval-model-tf-recommender"
  }
}