{ "id": 255239, "title": "[Compilation] SETI Breakthrough Listen - E.T. Signal Search : Starter Notebooks", "url": "/competitions/seti-breakthrough-listen/discussion/255239", "author_name": "KritiDoneria", "post_date": "2021-07-26T14:15:23.745000", "votes": 23, "comment_count": 0, "views": 0, "content": "
    \n

  1. EDA by GM @ihelpn

    2. \n

  2. A good end to end notebook by harshsharma511

    3. \n

  3. PyTorch NFNet starter by @yasufuminakama

    4. \n

  4. Pytorch starter by @piantic

    5. \n

  5. A great explanation and Baseline by GM @usharengaraju

    6. \n

  6. K Means clustering by @woosungyoon

    7. \n

  7. Augly by FB Demo by @shanmukh05. This is a must to check out for data augmentation alone.

    8. \n

  8. AutoKeras in action by @gaetanpelletier

    9. \n
\n

A huge shoutout to all these people who risk their LB positions in the spirit of community.
\nPlease upvote their notebooks if you find it useful.
\nThanks

", "messages": [ { "id": 1400699, "postDate": "2021-07-26T14:15:23.747Z", "content": "
    \n

  1. EDA by GM @ihelpn

    2. \n

  2. A good end to end notebook by harshsharma511

    3. \n

  3. PyTorch NFNet starter by @yasufuminakama

    4. \n

  4. Pytorch starter by @piantic

    5. \n

  5. A great explanation and Baseline by GM @usharengaraju

    6. \n

  6. K Means clustering by @woosungyoon

    7. \n

  7. Augly by FB Demo by @shanmukh05. This is a must to check out for data augmentation alone.

    8. \n

  8. AutoKeras in action by @gaetanpelletier

    9. \n
\n

A huge shoutout to all these people who risk their LB positions in the spirit of community.
\nPlease upvote their notebooks if you find it useful.
\nThanks

", "rawMarkdown": "1. [EDA](https://www.kaggle.com/ihelon/signal-search-exploratory-data-analysis) by GM @ihelpn\n\n2. [A good end to end notebook](https://www.kaggle.com/harshsharma511/one-stop-understanding-eda-efficientnet) by harshsharma511\n\n3. [PyTorch NFNet starter](https://www.kaggle.com/yasufuminakama/seti-nfnet-l0-starter-training) by @yasufuminakama\n\n4. [Pytorch starter](https://www.kaggle.com/piantic/infer-seti-pytorch-starter-chans-vs-spatial) by @piantic\n\n5. [A great explanation and Baseline](https://www.kaggle.com/usharengaraju/seti-eda-baseline-tensorflow-and-tpu) by GM @usharengaraju \n\n6. [K Means clustering](https://www.kaggle.com/woosungyoon/seti-kmean-clustering) by @woosungyoon\n\n7. [Augly by FB Demo](https://www.kaggle.com/shanmukh05/augly-fair-s-new-data-augmentation-library) by @shanmukh05. This is a must to check out for data augmentation alone.\n\n8. [AutoKeras in action](https://www.kaggle.com/gaetanpelletier/seti-autokeras) by @gaetanpelletier\n\n\nA huge shoutout to all these people who risk their LB positions in the spirit of community.\nPlease upvote their notebooks if you find it useful.\nThanks", "votes": 23 } ], "comments": [], "raw_markdown_by_id": { "1400699": "1. [EDA](https://www.kaggle.com/ihelon/signal-search-exploratory-data-analysis) by GM @ihelpn\n\n2. [A good end to end notebook](https://www.kaggle.com/harshsharma511/one-stop-understanding-eda-efficientnet) by harshsharma511\n\n3. [PyTorch NFNet starter](https://www.kaggle.com/yasufuminakama/seti-nfnet-l0-starter-training) by @yasufuminakama\n\n4. [Pytorch starter](https://www.kaggle.com/piantic/infer-seti-pytorch-starter-chans-vs-spatial) by @piantic\n\n5. [A great explanation and Baseline](https://www.kaggle.com/usharengaraju/seti-eda-baseline-tensorflow-and-tpu) by GM @usharengaraju \n\n6. [K Means clustering](https://www.kaggle.com/woosungyoon/seti-kmean-clustering) by @woosungyoon\n\n7. [Augly by FB Demo](https://www.kaggle.com/shanmukh05/augly-fair-s-new-data-augmentation-library) by @shanmukh05. This is a must to check out for data augmentation alone.\n\n8. [AutoKeras in action](https://www.kaggle.com/gaetanpelletier/seti-autokeras) by @gaetanpelletier\n\n\nA huge shoutout to all these people who risk their LB positions in the spirit of community.\nPlease upvote their notebooks if you find it useful.\nThanks" } }