Thanks for participating in this year’s BirdCLEF competition. Just like previous editions, this year’s challenge focuses on the science of recognizing birds by sound. There has been significant progress in this area of research in recent years, but we are not there yet. To make things a bit easier, we collected some resourced that will give you a head start. We have host notebooks that cover the basics, we have a great collection of 2020 write-ups, and we have very popular 2020 notebooks and forum threads. Here we go:
\nHost notebooks:
\n2020 write-ups:
\n2020 popular notebooks:
\n2020 collected resources:
\n\nGood luck everyone! Feel free to add more interesting resources. In any case, make sure to check out last year’s competition.
", "messages": [ { "id": 1259693, "postDate": "2021-04-01T15:35:59.093Z", "content": "Thanks for participating in this year’s BirdCLEF competition. Just like previous editions, this year’s challenge focuses on the science of recognizing birds by sound. There has been significant progress in this area of research in recent years, but we are not there yet. To make things a bit easier, we collected some resourced that will give you a head start. We have host notebooks that cover the basics, we have a great collection of 2020 write-ups, and we have very popular 2020 notebooks and forum threads. Here we go:
\nHost notebooks:
\n2020 write-ups:
\n2020 popular notebooks:
\n2020 collected resources:
\n\nGood luck everyone! Feel free to add more interesting resources. In any case, make sure to check out last year’s competition.
", "rawMarkdown": "Thanks for participating in this year’s BirdCLEF competition. Just like previous editions, this year’s challenge focuses on the science of recognizing birds by sound. There has been significant progress in this area of research in recent years, but we are not there yet. To make things a bit easier, we collected some resourced that will give you a head start. We have host notebooks that cover the basics, we have a great collection of 2020 write-ups, and we have very popular 2020 notebooks and forum threads. Here we go:\n\nHost notebooks:\n\n- [Exploring the data](https://www.kaggle.com/stefankahl/birdclef2021-exploring-the-data)\n- [Audio processing](https://www.kaggle.com/stefankahl/birdclef2021-processing-audio-data)\n- [Model training](https://www.kaggle.com/stefankahl/birdclef2021-model-training)\n- [Sample submission](https://www.kaggle.com/stefankahl/birdclef2021-sample-submission)\n- [Efficient TF Input Pipeline](https://www.kaggle.com/tomdenton/birdclef2021-tfaudiodataset)\n\n2020 write-ups:\n\n- [1st place solution](https://www.kaggle.com/c/birdsong-recognition/discussion/183208)\n- [2nd place solution](https://www.kaggle.com/c/birdsong-recognition/discussion/183269)\n- [3rd place solution](https://www.kaggle.com/c/birdsong-recognition/discussion/183199)\n- [4th place solution](https://www.kaggle.com/c/birdsong-recognition/discussion/183339)\n- [5th place solution](https://www.kaggle.com/c/birdsong-recognition/discussion/183300)\n- [6th place solution](https://www.kaggle.com/c/birdsong-recognition/discussion/183204)\n- [7th place solution](https://www.kaggle.com/c/birdsong-recognition/discussion/183571)\n- [8th place solution](https://www.kaggle.com/c/birdsong-recognition/discussion/183223)\n- [9th place solution](https://www.kaggle.com/c/birdsong-recognition/discussion/183315)\n- [10th place solution](https://www.kaggle.com/c/birdsong-recognition/discussion/183407)\n\n2020 popular notebooks:\n\n- [Birdcall Recognition EDA and FE](https://www.kaggle.com/andradaolteanu/birdcall-recognition-eda-and-audio-fe)\n- [Introduction to Sound Event Detection](https://www.kaggle.com/hidehisaarai1213/introduction-to-sound-event-detection)\n- [Inference PyTorch ResNet Baseline](https://www.kaggle.com/hidehisaarai1213/inference-pytorch-birdcall-resnet-baseline)\n- [Training Birdsong Baseline ResNet50](https://www.kaggle.com/ttahara/training-birdsong-baseline-resnest50-fast)\n- [EDA and Audio Processing with Python](https://www.kaggle.com/parulpandey/eda-and-audio-processing-with-python)\n- [Birds Sounds EDA](https://www.kaggle.com/pavansanagapati/birds-sounds-eda-spotify-urban-sound-eda)\n\n2020 collected resources:\n\n- [Collected resources thread](https://www.kaggle.com/c/birdsong-recognition/discussion/158933)\n\nGood luck everyone! Feel free to add more interesting resources. In any case, make sure to check out [last year’s competition](https://www.kaggle.com/c/birdsong-recognition/overview).\n", "votes": 114 }, { "id": 1268785, "postDate": "2021-04-09T18:46:15.900Z", "content": "Your host notebooks are great, especially for people with no experience in audio classification.
\nI wish all host provide similar started kit in other scientific competitions. I hope you just set the bar everyone else wil have to meet from now on ;)
", "rawMarkdown": "Your host notebooks are great, especially for people with no experience in audio classification.\n\nI wish all host provide similar started kit in other scientific competitions. I hope you just set the bar everyone else wil have to meet from now on ;)", "votes": 9, "replies": [ { "id": 1269222, "postDate": "2021-04-10T09:59:43.727Z", "content": "Thanks :) We're trying to get as many people as possible to contribute to bioacoustics, and Kaggle seems like a very good place to do that.
", "rawMarkdown": "Thanks :) We're trying to get as many people as possible to contribute to bioacoustics, and Kaggle seems like a very good place to do that.", "votes": 6 } ] }, { "id": 1274517, "postDate": "2021-04-15T11:30:53.883Z", "content": "Since you mentioned the 2020 competition, let me ask you a question this discussion.
\nDoes the train data for this competition include data from previous competitions like this https://www.kaggle.com/c/birdsong-recognition/overview ?
\nIf it's not included, I'm considering adding it to the data.
\nThank you.
Yes and no :) We used the same selection heuristic to compile the training data. We also included more files this year. Yet, the pre-processing of the files is a bit different. However, there should be a lot of overlap between the 2020 and 2021 data. Nonetheless, feel free to combine the two if you think it would help you.
", "rawMarkdown": "Yes and no :) We used the same selection heuristic to compile the training data. We also included more files this year. Yet, the pre-processing of the files is a bit different. However, there should be a lot of overlap between the 2020 and 2021 data. Nonetheless, feel free to combine the two if you think it would help you.", "votes": 4 }, { "id": 1274541, "postDate": "2021-04-15T11:51:30.317Z", "content": "I think it is very important information that the preprocessing is different and largely duplicated.
\nThanks for the quick answer :)
@naoism this year all data is resampled at 32kHz. I don't think it was the case last year. I don't know if there are other differences.
", "rawMarkdown": "@naoism this year all data is resampled at 32kHz. I don't think it was the case last year. I don't know if there are other differences.\n", "votes": 3 }, { "id": 1275091, "postDate": "2021-04-15T23:06:25.657Z", "content": "Thank you for the information. So there doesn't seem to be much difference between last year's and this year's data.
\nI think the other small difference is the file extension. Last year it was \".mp3\", but this year it is \".ogg\".
Yes, last year we had wav files, we had xenocanto file as is. I guess the preprocessed them with resampling and save as ogg files.
", "rawMarkdown": "Yes, last year we had wav files, we had xenocanto file as is. I guess the preprocessed them with resampling and save as ogg files.", "votes": 2 }, { "id": 1275468, "postDate": "2021-04-16T10:30:29.267Z", "content": "I see, so preprocessing is not a problem. So, as long as we can find duplicates, we can increase the amount of data. Thank you for your comment. :)
\nBy the way, do you use any other data for your current score? Of course, if you don't want to say it, you don't have to answer it !
I prefer not to share anything about what I am doing, sorry. In Rainforest competition I had a great score with my first sub, I then shared some info about it, and it unlocked a number of people who passed me before competition end.
\nI will share after competition end as I usually do.
\nGood luck till then.
", "rawMarkdown": "I prefer not to share anything about what I am doing, sorry. In Rainforest competition I had a great score with my first sub, I then shared some info about it, and it unlocked a number of people who passed me before competition end.\n\nI will share after competition end as I usually do.\n\nGood luck till then.", "votes": 2 }, { "id": 1275515, "postDate": "2021-04-16T11:39:49.677Z", "content": "No problem. I'm sorry too.
\nI will try my best to catch up with your score first. I'm looking forward to your solution after the competition !
@cpmpml With respect to your above comment \", all data is resampled at 32kHz.\"I think the sampling rate is 22050 HZ. Please correct me if I am wrong.
", "rawMarkdown": "@cpmpml With respect to your above comment \", all data is resampled at 32kHz.\"I think the sampling rate is 22050 HZ. Please correct me if I am wrong." }, { "id": 1284855, "postDate": "2021-04-26T10:34:45.890Z", "content": "which sampling rate are you discussing? Sampling rate of which data to be precise?
\nSampling rate of this competition is 32kHz. Just load a sound file to check for yourself.
", "rawMarkdown": "which sampling rate are you discussing? Sampling rate of which data to be precise?\n\nSampling rate of this competition is 32kHz. Just load a sound file to check for yourself.\n\n", "votes": 1 }, { "id": 1285057, "postDate": "2021-04-26T14:30:54.860Z", "content": "22050 Hz is the default sample rate for librosa.load. So if the sample rate does not get specified when using librosa.load, then librosa will automatically resample to 22050 Hz, or such is my understanding.
\nMore info here: https://librosa.org/blog/2019/07/17/resample-on-load/
\nAs far as I've seen, all of the competition data files are indeed at 32 kHz, and specifying the sample rate appropriately when using librosa.load will maintain that.
", "rawMarkdown": "22050 Hz is the default sample rate for librosa.load. So if the sample rate does not get specified when using librosa.load, then librosa will automatically resample to 22050 Hz, or such is my understanding. \n\nMore info here: https://librosa.org/blog/2019/07/17/resample-on-load/\n\nAs far as I've seen, all of the competition data files are indeed at 32 kHz, and specifying the sample rate appropriately when using librosa.load will maintain that. ", "votes": 2 }, { "id": 1285141, "postDate": "2021-04-26T16:07:38.543Z", "content": "Indeed. From librosa load documentaion:
\n\n\nTo preserve the native sampling rate of the file, use sr=None.
\n
That's better than setting a sampling rate as you can detect if the file is sampled differently than what you expect (32 kHz here).
", "rawMarkdown": "Indeed. From [librosa load documentaion](https://librosa.org/doc/main/generated/librosa.load.html):\n\n> To preserve the native sampling rate of the file, use sr=None.\n\nThat's better than setting a sampling rate as you can detect if the file is sampled differently than what you expect (32 kHz here).\n\n\n", "votes": 1 }, { "id": 1285158, "postDate": "2021-04-26T16:25:39.907Z", "content": "Thanks, @cpmpml. Understood.
", "rawMarkdown": "Thanks, @cpmpml. Understood.", "votes": 1 } ] }, { "id": 1273423, "postDate": "2021-04-14T10:40:15.137Z", "content": "Taking my hat off, the most comprehensive help package I have ever seen!
", "rawMarkdown": "Taking my hat off, the most comprehensive help package I have ever seen!", "votes": 1 }, { "id": 1260890, "postDate": "2021-04-02T13:57:46.163Z", "content": "Great start!
", "rawMarkdown": "Great start!", "votes": 1 }, { "id": 1263872, "postDate": "2021-04-05T18:26:52.977Z", "content": "Thanks for that compilation; lots of helpful info to work through. The link for the \"Comprehensive Feature Engineering Tutorial\" seems not to be working. Could you please check? Thank you!
", "rawMarkdown": "Thanks for that compilation; lots of helpful info to work through. The link for the \"Comprehensive Feature Engineering Tutorial\" seems not to be working. Could you please check? Thank you!", "votes": 2, "replies": [ { "id": 1264545, "postDate": "2021-04-06T08:37:22.543Z", "content": "Thanks for pointing this out. Seems like the name of the Notebook has changed. I updated the page and also added another host notebook.
", "rawMarkdown": "Thanks for pointing this out. Seems like the name of the Notebook has changed. I updated the page and also added another host notebook." } ] }, { "id": 1302785, "postDate": "2021-05-11T17:53:24.673Z", "content": "So, from what I understand after looking at the provided info, we submit a program that creates a csv formated file titled Submission.csv with all of the predictions for the TRAINING dataset?
", "rawMarkdown": "So, from what I understand after looking at the provided info, we submit a program that creates a csv formated file titled Submission.csv with all of the predictions for the TRAINING dataset?" }, { "id": 1287873, "postDate": "2021-04-29T13:35:01.027Z", "content": "Hi,
\nThis is my first machine learning Kaggle competition and I am pretty excited, but I am a bit confused as to the submission process. Am I required to write up a script that will train the model and predict on the hidden data, or maybe put the network in a function that returns the model's weights, or something about a spreadsheet with my model's predictions? Any help would be appreciated, thanks!!
Is it possible for beginners who have completed the Titanic competition and Tabular Playground Series --April 2021 to get results like winning medals in this competition with this wonderful information?
\nAs a graduate student, I have a lot of time.
@medhavi34 read this.
", "rawMarkdown": "@medhavi34 read this." }, { "id": 1260028, "postDate": "2021-04-01T19:24:38.183Z", "content": "Thank you so much! This is a helpful compilation!
", "rawMarkdown": "Thank you so much! This is a helpful compilation!" }, { "id": 1583219, "postDate": "2021-11-15T16:25:35.590Z", "content": "This has been helpful. Thank you.
", "rawMarkdown": "This has been helpful. Thank you.", "votes": 1 }, { "id": 1265270, "postDate": "2021-04-06T18:39:35.107Z", "content": "Thank you so much.
", "rawMarkdown": "Thank you so much." } ], "comments": [ { "id": 1268785, "author_name": "CPMP", "author_url": "", "post_date": "2021-04-09T18:46:15.900000", "content": "Your host notebooks are great, especially for people with no experience in audio classification.
\nI wish all host provide similar started kit in other scientific competitions. I hope you just set the bar everyone else wil have to meet from now on ;)
", "votes": 9, "replies": [ { "id": 1269222, "author_name": "Stefan Kahl", "author_url": "", "post_date": "2021-04-10T09:59:43.727000", "content": "Thanks :) We're trying to get as many people as possible to contribute to bioacoustics, and Kaggle seems like a very good place to do that.
", "votes": 6, "replies": [] } ] }, { "id": 1274517, "author_name": "Naoism", "author_url": "", "post_date": "2021-04-15T11:30:53.883000", "content": "Since you mentioned the 2020 competition, let me ask you a question this discussion.
\nDoes the train data for this competition include data from previous competitions like this https://www.kaggle.com/c/birdsong-recognition/overview ?
\nIf it's not included, I'm considering adding it to the data.
\nThank you.
Yes and no :) We used the same selection heuristic to compile the training data. We also included more files this year. Yet, the pre-processing of the files is a bit different. However, there should be a lot of overlap between the 2020 and 2021 data. Nonetheless, feel free to combine the two if you think it would help you.
", "votes": 4, "replies": [] }, { "id": 1274541, "author_name": "Naoism", "author_url": "", "post_date": "2021-04-15T11:51:30.317000", "content": "I think it is very important information that the preprocessing is different and largely duplicated.
\nThanks for the quick answer :)
@naoism this year all data is resampled at 32kHz. I don't think it was the case last year. I don't know if there are other differences.
", "votes": 3, "replies": [] }, { "id": 1275091, "author_name": "Naoism", "author_url": "", "post_date": "2021-04-15T23:06:25.657000", "content": "Thank you for the information. So there doesn't seem to be much difference between last year's and this year's data.
\nI think the other small difference is the file extension. Last year it was \".mp3\", but this year it is \".ogg\".
Yes, last year we had wav files, we had xenocanto file as is. I guess the preprocessed them with resampling and save as ogg files.
", "votes": 2, "replies": [] }, { "id": 1275468, "author_name": "Naoism", "author_url": "", "post_date": "2021-04-16T10:30:29.267000", "content": "I see, so preprocessing is not a problem. So, as long as we can find duplicates, we can increase the amount of data. Thank you for your comment. :)
\nBy the way, do you use any other data for your current score? Of course, if you don't want to say it, you don't have to answer it !
I prefer not to share anything about what I am doing, sorry. In Rainforest competition I had a great score with my first sub, I then shared some info about it, and it unlocked a number of people who passed me before competition end.
\nI will share after competition end as I usually do.
\nGood luck till then.
", "votes": 2, "replies": [] }, { "id": 1275515, "author_name": "Naoism", "author_url": "", "post_date": "2021-04-16T11:39:49.677000", "content": "No problem. I'm sorry too.
\nI will try my best to catch up with your score first. I'm looking forward to your solution after the competition !
@cpmpml With respect to your above comment \", all data is resampled at 32kHz.\"I think the sampling rate is 22050 HZ. Please correct me if I am wrong.
", "votes": 0, "replies": [] }, { "id": 1284855, "author_name": "CPMP", "author_url": "", "post_date": "2021-04-26T10:34:45.890000", "content": "which sampling rate are you discussing? Sampling rate of which data to be precise?
\nSampling rate of this competition is 32kHz. Just load a sound file to check for yourself.
", "votes": 1, "replies": [] }, { "id": 1285057, "author_name": "undisclosed", "author_url": "", "post_date": "2021-04-26T14:30:54.860000", "content": "22050 Hz is the default sample rate for librosa.load. So if the sample rate does not get specified when using librosa.load, then librosa will automatically resample to 22050 Hz, or such is my understanding.
\nMore info here: https://librosa.org/blog/2019/07/17/resample-on-load/
\nAs far as I've seen, all of the competition data files are indeed at 32 kHz, and specifying the sample rate appropriately when using librosa.load will maintain that.
", "votes": 2, "replies": [] }, { "id": 1285141, "author_name": "CPMP", "author_url": "", "post_date": "2021-04-26T16:07:38.543000", "content": "Indeed. From librosa load documentaion:
\n\n\nTo preserve the native sampling rate of the file, use sr=None.
\n
That's better than setting a sampling rate as you can detect if the file is sampled differently than what you expect (32 kHz here).
", "votes": 1, "replies": [] }, { "id": 1285158, "author_name": "Sachin Rastogi", "author_url": "", "post_date": "2021-04-26T16:25:39.907000", "content": "Thanks, @cpmpml. Understood.
", "votes": 1, "replies": [] } ] }, { "id": 1273423, "author_name": "Alex Kozlov", "author_url": "", "post_date": "2021-04-14T10:40:15.137000", "content": "Taking my hat off, the most comprehensive help package I have ever seen!
", "votes": 1, "replies": [] }, { "id": 1260890, "author_name": "Hugo Romano", "author_url": "", "post_date": "2021-04-02T13:57:46.163000", "content": "Great start!
", "votes": 1, "replies": [] }, { "id": 1263872, "author_name": "undisclosed", "author_url": "", "post_date": "2021-04-05T18:26:52.977000", "content": "Thanks for that compilation; lots of helpful info to work through. The link for the \"Comprehensive Feature Engineering Tutorial\" seems not to be working. Could you please check? Thank you!
", "votes": 2, "replies": [ { "id": 1264545, "author_name": "Stefan Kahl", "author_url": "", "post_date": "2021-04-06T08:37:22.543000", "content": "Thanks for pointing this out. Seems like the name of the Notebook has changed. I updated the page and also added another host notebook.
", "votes": 0, "replies": [] } ] }, { "id": 1302785, "author_name": "Tennis Ball", "author_url": "", "post_date": "2021-05-11T17:53:24.673000", "content": "So, from what I understand after looking at the provided info, we submit a program that creates a csv formated file titled Submission.csv with all of the predictions for the TRAINING dataset?
", "votes": 0, "replies": [] }, { "id": 1287873, "author_name": "Tennis Ball", "author_url": "", "post_date": "2021-04-29T13:35:01.027000", "content": "Hi,
\nThis is my first machine learning Kaggle competition and I am pretty excited, but I am a bit confused as to the submission process. Am I required to write up a script that will train the model and predict on the hidden data, or maybe put the network in a function that returns the model's weights, or something about a spreadsheet with my model's predictions? Any help would be appreciated, thanks!!
Is it possible for beginners who have completed the Titanic competition and Tabular Playground Series --April 2021 to get results like winning medals in this competition with this wonderful information?
\nAs a graduate student, I have a lot of time.
@medhavi34 read this.
", "votes": 0, "replies": [] }, { "id": 1260028, "author_name": "gradientBoost", "author_url": "", "post_date": "2021-04-01T19:24:38.183000", "content": "Thank you so much! This is a helpful compilation!
", "votes": 0, "replies": [] }, { "id": 1583219, "author_name": "Sean Buchanan", "author_url": "", "post_date": "2021-11-15T16:25:35.590000", "content": "This has been helpful. Thank you.
", "votes": 1, "replies": [] }, { "id": 1265270, "author_name": "MuniraShahir", "author_url": "", "post_date": "2021-04-06T18:39:35.107000", "content": "Thank you so much.
", "votes": 0, "replies": [] } ], "raw_markdown_by_id": { "1259693": "Thanks for participating in this year’s BirdCLEF competition. Just like previous editions, this year’s challenge focuses on the science of recognizing birds by sound. There has been significant progress in this area of research in recent years, but we are not there yet. To make things a bit easier, we collected some resourced that will give you a head start. We have host notebooks that cover the basics, we have a great collection of 2020 write-ups, and we have very popular 2020 notebooks and forum threads. Here we go:\n\nHost notebooks:\n\n- [Exploring the data](https://www.kaggle.com/stefankahl/birdclef2021-exploring-the-data)\n- [Audio processing](https://www.kaggle.com/stefankahl/birdclef2021-processing-audio-data)\n- [Model training](https://www.kaggle.com/stefankahl/birdclef2021-model-training)\n- [Sample submission](https://www.kaggle.com/stefankahl/birdclef2021-sample-submission)\n- [Efficient TF Input Pipeline](https://www.kaggle.com/tomdenton/birdclef2021-tfaudiodataset)\n\n2020 write-ups:\n\n- [1st place solution](https://www.kaggle.com/c/birdsong-recognition/discussion/183208)\n- [2nd place solution](https://www.kaggle.com/c/birdsong-recognition/discussion/183269)\n- [3rd place solution](https://www.kaggle.com/c/birdsong-recognition/discussion/183199)\n- [4th place solution](https://www.kaggle.com/c/birdsong-recognition/discussion/183339)\n- [5th place solution](https://www.kaggle.com/c/birdsong-recognition/discussion/183300)\n- [6th place solution](https://www.kaggle.com/c/birdsong-recognition/discussion/183204)\n- [7th place solution](https://www.kaggle.com/c/birdsong-recognition/discussion/183571)\n- [8th place solution](https://www.kaggle.com/c/birdsong-recognition/discussion/183223)\n- [9th place solution](https://www.kaggle.com/c/birdsong-recognition/discussion/183315)\n- [10th place solution](https://www.kaggle.com/c/birdsong-recognition/discussion/183407)\n\n2020 popular notebooks:\n\n- [Birdcall Recognition EDA and FE](https://www.kaggle.com/andradaolteanu/birdcall-recognition-eda-and-audio-fe)\n- [Introduction to Sound Event Detection](https://www.kaggle.com/hidehisaarai1213/introduction-to-sound-event-detection)\n- [Inference PyTorch ResNet Baseline](https://www.kaggle.com/hidehisaarai1213/inference-pytorch-birdcall-resnet-baseline)\n- [Training Birdsong Baseline ResNet50](https://www.kaggle.com/ttahara/training-birdsong-baseline-resnest50-fast)\n- [EDA and Audio Processing with Python](https://www.kaggle.com/parulpandey/eda-and-audio-processing-with-python)\n- [Birds Sounds EDA](https://www.kaggle.com/pavansanagapati/birds-sounds-eda-spotify-urban-sound-eda)\n\n2020 collected resources:\n\n- [Collected resources thread](https://www.kaggle.com/c/birdsong-recognition/discussion/158933)\n\nGood luck everyone! Feel free to add more interesting resources. In any case, make sure to check out [last year’s competition](https://www.kaggle.com/c/birdsong-recognition/overview).\n", "1268785": "Your host notebooks are great, especially for people with no experience in audio classification.\n\nI wish all host provide similar started kit in other scientific competitions. I hope you just set the bar everyone else wil have to meet from now on ;)", "1274517": "Since you mentioned the 2020 competition, let me ask you a question this discussion.\n\nDoes the train data for this competition include data from previous competitions like this [https://www.kaggle.com/c/birdsong-recognition/overview](url) ?\nIf it's not included, I'm considering adding it to the data.\nThank you.", "1273423": "Taking my hat off, the most comprehensive help package I have ever seen!", "1260890": "Great start!", "1263872": "Thanks for that compilation; lots of helpful info to work through. The link for the \"Comprehensive Feature Engineering Tutorial\" seems not to be working. Could you please check? Thank you!", "1302785": "So, from what I understand after looking at the provided info, we submit a program that creates a csv formated file titled Submission.csv with all of the predictions for the TRAINING dataset?", "1287873": "Hi,\nThis is my first machine learning Kaggle competition and I am pretty excited, but I am a bit confused as to the submission process. Am I required to write up a script that will train the model and predict on the hidden data, or maybe put the network in a function that returns the model's weights, or something about a spreadsheet with my model's predictions? Any help would be appreciated, thanks!!", "1286180": "Is it possible for beginners who have completed the Titanic competition and Tabular Playground Series --April 2021 to get results like winning medals in this competition with this wonderful information?\nAs a graduate student, I have a lot of time.", "1284989": "@medhavi34 read this.", "1260028": "Thank you so much! This is a helpful compilation!", "1583219": "This has been helpful. Thank you.", "1265270": "Thank you so much." } }