{ "id": 490862, "title": "Starter materials", "url": "/competitions/birdclef-2024/discussion/490862", "author_name": "", "post_date": "2024-04-03T18:49:57.974962300Z", "votes": 21, "comment_count": 1, "views": 0, "content": "

Hello all,

\n

I wish to extend sincere wishes to one and all for the challenge. Hope the below curated references may be of use to the participants-

\n

Similar assignments and artefacts

\n

GeoLifeCLEF 2024 @ LifeCLEF & CVPR-FGVC

\n

Kernels

\n
    \n
  1. https://www.kaggle.com/code/gobyeonggeon/preprocess-visualize-spatial-data-eda-xgb
    2. \n
  2. https://www.kaggle.com/code/mpwolke/glc2024-climaterasters-nir-pt-files
    3. \n
  3. https://www.kaggle.com/code/maximiliense/download-script-usage
    4. \n
\n

BirdCLEF 2023

\n

Highly voted kernels

\n
    \n
  1. https://www.kaggle.com/code/awsaf49/birdclef23-pretraining-is-all-you-need-train
    2. \n
  2. https://www.kaggle.com/code/awsaf49/birdclef23-pretraining-is-all-you-need-infer
    3. \n
  3. https://www.kaggle.com/code/awsaf49/birdclef23-effnet-fsr-cutmixup-train
    4. \n
  4. https://www.kaggle.com/code/burhanuddinlatsaheb/eda-visualizations-audio-exploration
    5. \n
  5. https://www.kaggle.com/code/leonidkulyk/eda-birdclef-plotly-vis-map-audio
    6. \n
  6. https://www.kaggle.com/code/nischaydnk/birdclef-2023-pytorch-lightning-training-w-cmap
    7. \n
\n

High scoring kernels

\n
    \n
  1. https://www.kaggle.com/code/mariotsaberlin/bc23-3rd-place-solution-refactored
    2. \n
  2. https://www.kaggle.com/code/atsunorifujita/4th-place-solution-inference-kernel
    3. \n
  3. https://www.kaggle.com/code/vladimirsydor/bird-clef-2023-inference-v1
    4. \n
  4. https://www.kaggle.com/code/evgeniimaslov2/birdclef-5th-place-code
    5. \n
  5. https://www.kaggle.com/code/leonshangguan/fork-of-fork-of-onnx-final-combine-bs4-b9daf6
    6. \n
\n

High scoring approaches

\n
    \n
  1. https://www.kaggle.com/competitions/birdclef-2023/discussion/412808 -- rank1
    2. \n
  2. https://www.kaggle.com/competitions/birdclef-2023/discussion/412707 -- rank2
    3. \n
  3. https://www.kaggle.com/competitions/birdclef-2023/discussion/414102 -- rank3
    4. \n
  4. https://www.kaggle.com/competitions/birdclef-2023/discussion/412753 -- rank4
    5. \n
  5. https://www.kaggle.com/competitions/birdclef-2023/discussion/412903 -- rank5
    6. \n
\n

BirdCLEF 2022

\n

Highly voted kernels

\n
    \n
  1. https://www.kaggle.com/code/shreyasajal/birdclef-librosa-audio-feature-extraction
    2. \n
  2. https://www.kaggle.com/code/awsaf49/birdclef23-pretraining-is-all-you-need-train
    3. \n
  3. https://www.kaggle.com/code/hasanbasriakcay/birdclef22-eda-noise-reduction
    4. \n
  4. https://www.kaggle.com/code/kaerunantoka/birdclef2022-ex005-f0-infer
    5. \n
  5. https://www.kaggle.com/code/julian3833/birdclef-21-2nd-place-model-submit-0-66
    6. \n
\n

High scoring kernels

\n
    \n
  1. https://www.kaggle.com/code/leonshangguan/birdnet-inference
    2. \n
  2. https://www.kaggle.com/code/ivanpan/fork-of-fork-of-cls-exp-1-870246-021187-967146
    3. \n
  3. https://www.kaggle.com/code/asaliquid1011/birdclef2022-3rd-place-inference
    4. \n
  4. https://www.kaggle.com/code/deepkim/22nd-private-0-76-public-0-82-submission
    5. \n
  5. https://www.kaggle.com/code/kunihikofurugori/birdclef2022-15th-solution
    6. \n
\n

High scoring approaches

\n
    \n
  1. https://www.kaggle.com/competitions/birdclef-2022/discussion/327047 -- rank1
    2. \n
  2. https://www.kaggle.com/competitions/birdclef-2022/discussion/326950 -- rank2
    3. \n
  3. https://www.kaggle.com/competitions/birdclef-2022/discussion/327193 -- rank3
    4. \n
  4. https://www.kaggle.com/competitions/birdclef-2022/discussion/326987 -- rank4
    5. \n
  5. https://www.kaggle.com/competitions/birdclef-2022/discussion/327044 -- rank5
    6. \n
  6. https://www.kaggle.com/competitions/birdclef-2022/discussion/327187 -- rank6
    7. \n
\n

BirdCLEF 2021 - Birdcall Identification

\n

Highly voted kernels

\n
    \n
  1. https://www.kaggle.com/code/kneroma/clean-fast-simple-bird-identifier-inference
    2. \n
  2. https://www.kaggle.com/code/shreyasajal/birdclef-librosa-audio-feature-extraction
    3. \n
  3. https://www.kaggle.com/code/awsaf49/birdclef23-pretraining-is-all-you-need-train
    4. \n
  4. https://www.kaggle.com/code/hidehisaarai1213/pytorch-training-birdclef2021-starter
    5. \n
  5. https://www.kaggle.com/code/kneroma/clean-fast-simple-bird-identifier-training-colab
    6. \n
\n

High scoring kernels

\n
    \n
  1. https://www.kaggle.com/code/ilu000/2nd-place-birdclef2021-inference
    2. \n
  2. https://www.kaggle.com/code/tattaka/birdclef2021-submissions-pp-ave
    3. \n
  3. https://www.kaggle.com/code/underwearfitting/bird-clef-final-ensemble-v2
    4. \n
  4. https://www.kaggle.com/code/hidehisaarai1213/birdclef2021-infer-between-chunk
    5. \n
  5. https://www.kaggle.com/code/nadyastrogankova/16-s-place-solution
    6. \n
\n

High scoring approaches

\n
    \n
  1. https://www.kaggle.com/competitions/birdclef-2021/discussion/243304 -- rank1
    2. \n
  2. https://www.kaggle.com/competitions/birdclef-2021/discussion/243463 -- rank2
    3. \n
  3. https://www.kaggle.com/competitions/birdclef-2021/discussion/245708 -- rank3
    4. \n
  4. https://www.kaggle.com/competitions/birdclef-2021/discussion/243293 -- rank4
    5. \n
  5. https://www.kaggle.com/competitions/birdclef-2021/discussion/243351 -- rank5
    6. \n
\n

Wishing all the participants the best and thanks to these content creators!
\nBest regards.

\n

P.S. Reminder to verify yourself to start herewith according to the new policy, please refer to the post here for details.

", "messages": [ { "id": "2733702", "postDate": "04/03/2024 18:49:57", "content": "

Hello all,

\n

I wish to extend sincere wishes to one and all for the challenge. Hope the below curated references may be of use to the participants-

\n

Similar assignments and artefacts

\n

GeoLifeCLEF 2024 @ LifeCLEF & CVPR-FGVC

\n

Kernels

\n
    \n
  1. https://www.kaggle.com/code/gobyeonggeon/preprocess-visualize-spatial-data-eda-xgb
    2. \n
  2. https://www.kaggle.com/code/mpwolke/glc2024-climaterasters-nir-pt-files
    3. \n
  3. https://www.kaggle.com/code/maximiliense/download-script-usage
    4. \n
\n

BirdCLEF 2023

\n

Highly voted kernels

\n
    \n
  1. https://www.kaggle.com/code/awsaf49/birdclef23-pretraining-is-all-you-need-train
    2. \n
  2. https://www.kaggle.com/code/awsaf49/birdclef23-pretraining-is-all-you-need-infer
    3. \n
  3. https://www.kaggle.com/code/awsaf49/birdclef23-effnet-fsr-cutmixup-train
    4. \n
  4. https://www.kaggle.com/code/burhanuddinlatsaheb/eda-visualizations-audio-exploration
    5. \n
  5. https://www.kaggle.com/code/leonidkulyk/eda-birdclef-plotly-vis-map-audio
    6. \n
  6. https://www.kaggle.com/code/nischaydnk/birdclef-2023-pytorch-lightning-training-w-cmap
    7. \n
\n

High scoring kernels

\n
    \n
  1. https://www.kaggle.com/code/mariotsaberlin/bc23-3rd-place-solution-refactored
    2. \n
  2. https://www.kaggle.com/code/atsunorifujita/4th-place-solution-inference-kernel
    3. \n
  3. https://www.kaggle.com/code/vladimirsydor/bird-clef-2023-inference-v1
    4. \n
  4. https://www.kaggle.com/code/evgeniimaslov2/birdclef-5th-place-code
    5. \n
  5. https://www.kaggle.com/code/leonshangguan/fork-of-fork-of-onnx-final-combine-bs4-b9daf6
    6. \n
\n

High scoring approaches

\n
    \n
  1. https://www.kaggle.com/competitions/birdclef-2023/discussion/412808 -- rank1
    2. \n
  2. https://www.kaggle.com/competitions/birdclef-2023/discussion/412707 -- rank2
    3. \n
  3. https://www.kaggle.com/competitions/birdclef-2023/discussion/414102 -- rank3
    4. \n
  4. https://www.kaggle.com/competitions/birdclef-2023/discussion/412753 -- rank4
    5. \n
  5. https://www.kaggle.com/competitions/birdclef-2023/discussion/412903 -- rank5
    6. \n
\n

BirdCLEF 2022

\n

Highly voted kernels

\n
    \n
  1. https://www.kaggle.com/code/shreyasajal/birdclef-librosa-audio-feature-extraction
    2. \n
  2. https://www.kaggle.com/code/awsaf49/birdclef23-pretraining-is-all-you-need-train
    3. \n
  3. https://www.kaggle.com/code/hasanbasriakcay/birdclef22-eda-noise-reduction
    4. \n
  4. https://www.kaggle.com/code/kaerunantoka/birdclef2022-ex005-f0-infer
    5. \n
  5. https://www.kaggle.com/code/julian3833/birdclef-21-2nd-place-model-submit-0-66
    6. \n
\n

High scoring kernels

\n
    \n
  1. https://www.kaggle.com/code/leonshangguan/birdnet-inference
    2. \n
  2. https://www.kaggle.com/code/ivanpan/fork-of-fork-of-cls-exp-1-870246-021187-967146
    3. \n
  3. https://www.kaggle.com/code/asaliquid1011/birdclef2022-3rd-place-inference
    4. \n
  4. https://www.kaggle.com/code/deepkim/22nd-private-0-76-public-0-82-submission
    5. \n
  5. https://www.kaggle.com/code/kunihikofurugori/birdclef2022-15th-solution
    6. \n
\n

High scoring approaches

\n
    \n
  1. https://www.kaggle.com/competitions/birdclef-2022/discussion/327047 -- rank1
    2. \n
  2. https://www.kaggle.com/competitions/birdclef-2022/discussion/326950 -- rank2
    3. \n
  3. https://www.kaggle.com/competitions/birdclef-2022/discussion/327193 -- rank3
    4. \n
  4. https://www.kaggle.com/competitions/birdclef-2022/discussion/326987 -- rank4
    5. \n
  5. https://www.kaggle.com/competitions/birdclef-2022/discussion/327044 -- rank5
    6. \n
  6. https://www.kaggle.com/competitions/birdclef-2022/discussion/327187 -- rank6
    7. \n
\n

BirdCLEF 2021 - Birdcall Identification

\n

Highly voted kernels

\n
    \n
  1. https://www.kaggle.com/code/kneroma/clean-fast-simple-bird-identifier-inference
    2. \n
  2. https://www.kaggle.com/code/shreyasajal/birdclef-librosa-audio-feature-extraction
    3. \n
  3. https://www.kaggle.com/code/awsaf49/birdclef23-pretraining-is-all-you-need-train
    4. \n
  4. https://www.kaggle.com/code/hidehisaarai1213/pytorch-training-birdclef2021-starter
    5. \n
  5. https://www.kaggle.com/code/kneroma/clean-fast-simple-bird-identifier-training-colab
    6. \n
\n

High scoring kernels

\n
    \n
  1. https://www.kaggle.com/code/ilu000/2nd-place-birdclef2021-inference
    2. \n
  2. https://www.kaggle.com/code/tattaka/birdclef2021-submissions-pp-ave
    3. \n
  3. https://www.kaggle.com/code/underwearfitting/bird-clef-final-ensemble-v2
    4. \n
  4. https://www.kaggle.com/code/hidehisaarai1213/birdclef2021-infer-between-chunk
    5. \n
  5. https://www.kaggle.com/code/nadyastrogankova/16-s-place-solution
    6. \n
\n

High scoring approaches

\n
    \n
  1. https://www.kaggle.com/competitions/birdclef-2021/discussion/243304 -- rank1
    2. \n
  2. https://www.kaggle.com/competitions/birdclef-2021/discussion/243463 -- rank2
    3. \n
  3. https://www.kaggle.com/competitions/birdclef-2021/discussion/245708 -- rank3
    4. \n
  4. https://www.kaggle.com/competitions/birdclef-2021/discussion/243293 -- rank4
    5. \n
  5. https://www.kaggle.com/competitions/birdclef-2021/discussion/243351 -- rank5
    6. \n
\n

Wishing all the participants the best and thanks to these content creators!
\nBest regards.

\n

P.S. Reminder to verify yourself to start herewith according to the new policy, please refer to the post here for details.

", "rawMarkdown": "Hello all,\n\nI wish to extend sincere wishes to one and all for the challenge. Hope the below curated references may be of use to the participants-\n\n# Similar assignments and artefacts\n## [GeoLifeCLEF 2024 @ LifeCLEF & CVPR-FGVC](https://www.kaggle.com/competitions/geolifeclef-2024)\n### Kernels\n1. https://www.kaggle.com/code/gobyeonggeon/preprocess-visualize-spatial-data-eda-xgb\n2. https://www.kaggle.com/code/mpwolke/glc2024-climaterasters-nir-pt-files\n3. https://www.kaggle.com/code/maximiliense/download-script-usage\n\n## [BirdCLEF 2023](https://www.kaggle.com/competitions/birdclef-2023)\n### Highly voted kernels \n1. https://www.kaggle.com/code/awsaf49/birdclef23-pretraining-is-all-you-need-train\n2. https://www.kaggle.com/code/awsaf49/birdclef23-pretraining-is-all-you-need-infer\n3. https://www.kaggle.com/code/awsaf49/birdclef23-effnet-fsr-cutmixup-train\n4. https://www.kaggle.com/code/burhanuddinlatsaheb/eda-visualizations-audio-exploration\n5. https://www.kaggle.com/code/leonidkulyk/eda-birdclef-plotly-vis-map-audio\n6. https://www.kaggle.com/code/nischaydnk/birdclef-2023-pytorch-lightning-training-w-cmap\n\n### High scoring kernels \n1. https://www.kaggle.com/code/mariotsaberlin/bc23-3rd-place-solution-refactored\n2. https://www.kaggle.com/code/atsunorifujita/4th-place-solution-inference-kernel\n3. https://www.kaggle.com/code/vladimirsydor/bird-clef-2023-inference-v1\n4. https://www.kaggle.com/code/evgeniimaslov2/birdclef-5th-place-code\n5. https://www.kaggle.com/code/leonshangguan/fork-of-fork-of-onnx-final-combine-bs4-b9daf6\n\n### High scoring approaches\n1. https://www.kaggle.com/competitions/birdclef-2023/discussion/412808 -- rank1\n2. https://www.kaggle.com/competitions/birdclef-2023/discussion/412707 -- rank2\n3. https://www.kaggle.com/competitions/birdclef-2023/discussion/414102 -- rank3\n4. https://www.kaggle.com/competitions/birdclef-2023/discussion/412753 -- rank4\n5. https://www.kaggle.com/competitions/birdclef-2023/discussion/412903 -- rank5\n\n## [BirdCLEF 2022](https://www.kaggle.com/competitions/birdclef-2022)\n### Highly voted kernels \n1. https://www.kaggle.com/code/shreyasajal/birdclef-librosa-audio-feature-extraction\n2. https://www.kaggle.com/code/awsaf49/birdclef23-pretraining-is-all-you-need-train\n3. https://www.kaggle.com/code/hasanbasriakcay/birdclef22-eda-noise-reduction\n4. https://www.kaggle.com/code/kaerunantoka/birdclef2022-ex005-f0-infer\n5. https://www.kaggle.com/code/julian3833/birdclef-21-2nd-place-model-submit-0-66\n\n### High scoring kernels \n1. https://www.kaggle.com/code/leonshangguan/birdnet-inference\n2. https://www.kaggle.com/code/ivanpan/fork-of-fork-of-cls-exp-1-870246-021187-967146\n3. https://www.kaggle.com/code/asaliquid1011/birdclef2022-3rd-place-inference\n4. https://www.kaggle.com/code/deepkim/22nd-private-0-76-public-0-82-submission\n5. https://www.kaggle.com/code/kunihikofurugori/birdclef2022-15th-solution\n\n### High scoring approaches \n1. https://www.kaggle.com/competitions/birdclef-2022/discussion/327047 -- rank1\n2. https://www.kaggle.com/competitions/birdclef-2022/discussion/326950 -- rank2\n3. https://www.kaggle.com/competitions/birdclef-2022/discussion/327193 -- rank3\n4. https://www.kaggle.com/competitions/birdclef-2022/discussion/326987 -- rank4\n5. https://www.kaggle.com/competitions/birdclef-2022/discussion/327044 -- rank5\n6. https://www.kaggle.com/competitions/birdclef-2022/discussion/327187 -- rank6\n\n## [BirdCLEF 2021 - Birdcall Identification](https://www.kaggle.com/competitions/birdclef-2021)\n### Highly voted kernels \n1. https://www.kaggle.com/code/kneroma/clean-fast-simple-bird-identifier-inference\n2. https://www.kaggle.com/code/shreyasajal/birdclef-librosa-audio-feature-extraction\n3. https://www.kaggle.com/code/awsaf49/birdclef23-pretraining-is-all-you-need-train\n4. https://www.kaggle.com/code/hidehisaarai1213/pytorch-training-birdclef2021-starter\n5. https://www.kaggle.com/code/kneroma/clean-fast-simple-bird-identifier-training-colab\n\n### High scoring kernels \n1. https://www.kaggle.com/code/ilu000/2nd-place-birdclef2021-inference\n2. https://www.kaggle.com/code/tattaka/birdclef2021-submissions-pp-ave\n3. https://www.kaggle.com/code/underwearfitting/bird-clef-final-ensemble-v2\n4. https://www.kaggle.com/code/hidehisaarai1213/birdclef2021-infer-between-chunk\n5. https://www.kaggle.com/code/nadyastrogankova/16-s-place-solution\n\n### High scoring approaches\n1. https://www.kaggle.com/competitions/birdclef-2021/discussion/243304 -- rank1\n2. https://www.kaggle.com/competitions/birdclef-2021/discussion/243463 -- rank2\n3. https://www.kaggle.com/competitions/birdclef-2021/discussion/245708 -- rank3\n4. https://www.kaggle.com/competitions/birdclef-2021/discussion/243293 -- rank4\n5. https://www.kaggle.com/competitions/birdclef-2021/discussion/243351 -- rank5\n\nWishing all the participants the best and thanks to these content creators!\nBest regards.\n\nP.S. Reminder to verify yourself to start herewith according to the new policy, please refer to the post [here](https://www.kaggle.com/discussions/general/490841) for details.", "votes": null }, { "id": "2734675", "postDate": "04/04/2024 08:42:48", "content": "

Thank you for this useful starter info @ravi20076

", "rawMarkdown": "Thank you for this useful starter info @ravi20076", "votes": null } ], "comments": [ { "id": 2734675, "author_name": "sahirmaharajj", "author_url": "", "post_date": "04/04/2024 08:42:48", "content": "

Thank you for this useful starter info @ravi20076

", "votes": null, "replies": [] } ], "raw_markdown_by_id": { "2733702": "Hello all,\n\nI wish to extend sincere wishes to one and all for the challenge. Hope the below curated references may be of use to the participants-\n\n# Similar assignments and artefacts\n## [GeoLifeCLEF 2024 @ LifeCLEF & CVPR-FGVC](https://www.kaggle.com/competitions/geolifeclef-2024)\n### Kernels\n1. https://www.kaggle.com/code/gobyeonggeon/preprocess-visualize-spatial-data-eda-xgb\n2. https://www.kaggle.com/code/mpwolke/glc2024-climaterasters-nir-pt-files\n3. https://www.kaggle.com/code/maximiliense/download-script-usage\n\n## [BirdCLEF 2023](https://www.kaggle.com/competitions/birdclef-2023)\n### Highly voted kernels \n1. https://www.kaggle.com/code/awsaf49/birdclef23-pretraining-is-all-you-need-train\n2. https://www.kaggle.com/code/awsaf49/birdclef23-pretraining-is-all-you-need-infer\n3. https://www.kaggle.com/code/awsaf49/birdclef23-effnet-fsr-cutmixup-train\n4. https://www.kaggle.com/code/burhanuddinlatsaheb/eda-visualizations-audio-exploration\n5. https://www.kaggle.com/code/leonidkulyk/eda-birdclef-plotly-vis-map-audio\n6. https://www.kaggle.com/code/nischaydnk/birdclef-2023-pytorch-lightning-training-w-cmap\n\n### High scoring kernels \n1. https://www.kaggle.com/code/mariotsaberlin/bc23-3rd-place-solution-refactored\n2. https://www.kaggle.com/code/atsunorifujita/4th-place-solution-inference-kernel\n3. https://www.kaggle.com/code/vladimirsydor/bird-clef-2023-inference-v1\n4. https://www.kaggle.com/code/evgeniimaslov2/birdclef-5th-place-code\n5. https://www.kaggle.com/code/leonshangguan/fork-of-fork-of-onnx-final-combine-bs4-b9daf6\n\n### High scoring approaches\n1. https://www.kaggle.com/competitions/birdclef-2023/discussion/412808 -- rank1\n2. https://www.kaggle.com/competitions/birdclef-2023/discussion/412707 -- rank2\n3. https://www.kaggle.com/competitions/birdclef-2023/discussion/414102 -- rank3\n4. https://www.kaggle.com/competitions/birdclef-2023/discussion/412753 -- rank4\n5. https://www.kaggle.com/competitions/birdclef-2023/discussion/412903 -- rank5\n\n## [BirdCLEF 2022](https://www.kaggle.com/competitions/birdclef-2022)\n### Highly voted kernels \n1. https://www.kaggle.com/code/shreyasajal/birdclef-librosa-audio-feature-extraction\n2. https://www.kaggle.com/code/awsaf49/birdclef23-pretraining-is-all-you-need-train\n3. https://www.kaggle.com/code/hasanbasriakcay/birdclef22-eda-noise-reduction\n4. https://www.kaggle.com/code/kaerunantoka/birdclef2022-ex005-f0-infer\n5. https://www.kaggle.com/code/julian3833/birdclef-21-2nd-place-model-submit-0-66\n\n### High scoring kernels \n1. https://www.kaggle.com/code/leonshangguan/birdnet-inference\n2. https://www.kaggle.com/code/ivanpan/fork-of-fork-of-cls-exp-1-870246-021187-967146\n3. https://www.kaggle.com/code/asaliquid1011/birdclef2022-3rd-place-inference\n4. https://www.kaggle.com/code/deepkim/22nd-private-0-76-public-0-82-submission\n5. https://www.kaggle.com/code/kunihikofurugori/birdclef2022-15th-solution\n\n### High scoring approaches \n1. https://www.kaggle.com/competitions/birdclef-2022/discussion/327047 -- rank1\n2. https://www.kaggle.com/competitions/birdclef-2022/discussion/326950 -- rank2\n3. https://www.kaggle.com/competitions/birdclef-2022/discussion/327193 -- rank3\n4. https://www.kaggle.com/competitions/birdclef-2022/discussion/326987 -- rank4\n5. https://www.kaggle.com/competitions/birdclef-2022/discussion/327044 -- rank5\n6. https://www.kaggle.com/competitions/birdclef-2022/discussion/327187 -- rank6\n\n## [BirdCLEF 2021 - Birdcall Identification](https://www.kaggle.com/competitions/birdclef-2021)\n### Highly voted kernels \n1. https://www.kaggle.com/code/kneroma/clean-fast-simple-bird-identifier-inference\n2. https://www.kaggle.com/code/shreyasajal/birdclef-librosa-audio-feature-extraction\n3. https://www.kaggle.com/code/awsaf49/birdclef23-pretraining-is-all-you-need-train\n4. https://www.kaggle.com/code/hidehisaarai1213/pytorch-training-birdclef2021-starter\n5. https://www.kaggle.com/code/kneroma/clean-fast-simple-bird-identifier-training-colab\n\n### High scoring kernels \n1. https://www.kaggle.com/code/ilu000/2nd-place-birdclef2021-inference\n2. https://www.kaggle.com/code/tattaka/birdclef2021-submissions-pp-ave\n3. https://www.kaggle.com/code/underwearfitting/bird-clef-final-ensemble-v2\n4. https://www.kaggle.com/code/hidehisaarai1213/birdclef2021-infer-between-chunk\n5. https://www.kaggle.com/code/nadyastrogankova/16-s-place-solution\n\n### High scoring approaches\n1. https://www.kaggle.com/competitions/birdclef-2021/discussion/243304 -- rank1\n2. https://www.kaggle.com/competitions/birdclef-2021/discussion/243463 -- rank2\n3. https://www.kaggle.com/competitions/birdclef-2021/discussion/245708 -- rank3\n4. https://www.kaggle.com/competitions/birdclef-2021/discussion/243293 -- rank4\n5. https://www.kaggle.com/competitions/birdclef-2021/discussion/243351 -- rank5\n\nWishing all the participants the best and thanks to these content creators!\nBest regards.\n\nP.S. Reminder to verify yourself to start herewith according to the new policy, please refer to the post [here](https://www.kaggle.com/discussions/general/490841) for details.", "2734675": "Thank you for this useful starter info @ravi20076" }, "source": "meta" }