We have some very interesting public notebooks from our last GSDC competition. Some of them might be useful for this competition as well.
\nAlso, fifth place team from the last GSDC shared their solution notebooks listed below which would be very helpful for us.
\nThe detailed solution approach can be seen in this forum post
\nPlease share any additional interesting notebooks from the last competition in comments. Thank you.
", "messages": [ { "id": "1775777", "postDate": "05/03/2022 11:45:46", "content": "We have some very interesting public notebooks from our last GSDC competition. Some of them might be useful for this competition as well.
\nAlso, fifth place team from the last GSDC shared their solution notebooks listed below which would be very helpful for us.
\nThe detailed solution approach can be seen in this forum post
\nPlease share any additional interesting notebooks from the last competition in comments. Thank you.
", "rawMarkdown": "We have some very interesting public notebooks from our last GSDC competition. Some of them might be useful for this competition as well.\n\n* [Let's visualize dataset to understand! πδΈ](https://www.kaggle.com/code/nayuts/let-s-visualize-dataset-to-understand) - A very extensive EDA on the dataset with some cool plots.\n* [Demonstration of the Kalman filter](https://www.kaggle.com/code/emaerthin/demonstration-of-the-kalman-filter/notebook) - Demonstrates how Kalman filter can be applied to improve the baseline results. \n* [GSDC: Position shift](https://www.kaggle.com/code/wrrosa/gsdc-position-shift/notebook) - This notebook shows how to apply position shift respectively to course.Β \n* [Road detection and creating grid points](https://www.kaggle.com/code/kuto0633/road-detection-and-creating-grid-points) - This notebooks shows how to detect road from open street map and how to create grid points from road data.\n* [GSDC EDA : Error when stopping](https://www.kaggle.com/code/t88take/gsdc-eda-error-when-stopping/notebook) - This notebook shows the error analysis when the car is stopping.\n* [Loading GNSS logs](https://www.kaggle.com/code/sohier/loading-gnss-logs) - This notebook provides a handy function to load the GNSS data into pandas data frames.\n* [Tips/Notes from the Competition Hosts](https://www.kaggle.com/code/gymf123/tips-notes-from-the-competition-hosts) - Competition hosts shared some tips and notes during the last competition which is present in this notebook\n* [Data divided into 3 areas(downtown,highway,tree)](https://www.kaggle.com/code/tyonemoto/data-divided-into-3-areas-downtown-highway-tree) - The data is divided into three areas and the evaluation is done for each of them separately.\n\nAlso, fifth place team from the last GSDC shared their solution notebooks listed below which would be very helpful for us. \n* [GSDC - Optimization based smoothing (1st version)](https://www.kaggle.com/code/saitodevel01/gsdc-optimization-based-smoothing-1st-version/notebook)\n* [GSDC - Vehicle Speed Estimation by Doppler Shift](https://www.kaggle.com/code/saitodevel01/gsdc-vehicle-speed-estimation-by-doppler-shift/notebook)\n* [GSDC - Improved Raw GNSS Baseline](https://www.kaggle.com/code/saitodevel01/gsdc-improved-raw-gnss-baseline/notebook)\n* [DSDC - Unified post-processing](https://www.kaggle.com/code/saitodevel01/dsdc-unified-post-processing/notebook)\n* [GSDC - Bias EDA](https://www.kaggle.com/code/saitodevel01/gsdc-bias-eda/notebook)\n* [GSDC - Bias Correction](https://www.kaggle.com/code/saitodevel01/gsdc-bias-correction/notebook)\n\nThe detailed solution approach can be seen in [this forum post](https://www.kaggle.com/c/google-smartphone-decimeter-challenge/discussion/261959)\n\nPlease share any additional interesting notebooks from the last competition in comments. Thank you.", "votes": null }, { "id": "1775875", "postDate": "05/03/2022 13:32:07", "content": "A great roundup of helpful notebooks from the last GSDC competition! This is a great resource for anyone looking to get started in the competition.
", "rawMarkdown": "A great roundup of helpful notebooks from the last GSDC competition! This is a great resource for anyone looking to get started in the competition.", "votes": null }, { "id": "1811054", "postDate": "06/04/2022 08:35:35", "content": "Thank you for a very nice collection of notebooks.
\nVery useful as I did not attend the last GSDC.
Thanks SRk for giving the overview to reach to the goals.
", "rawMarkdown": "Thanks SRk for giving the overview to reach to the goals.", "votes": null } ], "comments": [ { "id": 1775875, "author_name": "", "author_url": "", "post_date": "05/03/2022 13:32:07", "content": "A great roundup of helpful notebooks from the last GSDC competition! This is a great resource for anyone looking to get started in the competition.
", "votes": null, "replies": [] }, { "id": 1811054, "author_name": "minfuka", "author_url": "", "post_date": "06/04/2022 08:35:35", "content": "Thank you for a very nice collection of notebooks.
\nVery useful as I did not attend the last GSDC.
Thanks SRk for giving the overview to reach to the goals.
", "votes": null, "replies": [] } ], "raw_markdown_by_id": { "1775777": "We have some very interesting public notebooks from our last GSDC competition. Some of them might be useful for this competition as well.\n\n* [Let's visualize dataset to understand! πδΈ](https://www.kaggle.com/code/nayuts/let-s-visualize-dataset-to-understand) - A very extensive EDA on the dataset with some cool plots.\n* [Demonstration of the Kalman filter](https://www.kaggle.com/code/emaerthin/demonstration-of-the-kalman-filter/notebook) - Demonstrates how Kalman filter can be applied to improve the baseline results. \n* [GSDC: Position shift](https://www.kaggle.com/code/wrrosa/gsdc-position-shift/notebook) - This notebook shows how to apply position shift respectively to course.Β \n* [Road detection and creating grid points](https://www.kaggle.com/code/kuto0633/road-detection-and-creating-grid-points) - This notebooks shows how to detect road from open street map and how to create grid points from road data.\n* [GSDC EDA : Error when stopping](https://www.kaggle.com/code/t88take/gsdc-eda-error-when-stopping/notebook) - This notebook shows the error analysis when the car is stopping.\n* [Loading GNSS logs](https://www.kaggle.com/code/sohier/loading-gnss-logs) - This notebook provides a handy function to load the GNSS data into pandas data frames.\n* [Tips/Notes from the Competition Hosts](https://www.kaggle.com/code/gymf123/tips-notes-from-the-competition-hosts) - Competition hosts shared some tips and notes during the last competition which is present in this notebook\n* [Data divided into 3 areas(downtown,highway,tree)](https://www.kaggle.com/code/tyonemoto/data-divided-into-3-areas-downtown-highway-tree) - The data is divided into three areas and the evaluation is done for each of them separately.\n\nAlso, fifth place team from the last GSDC shared their solution notebooks listed below which would be very helpful for us. \n* [GSDC - Optimization based smoothing (1st version)](https://www.kaggle.com/code/saitodevel01/gsdc-optimization-based-smoothing-1st-version/notebook)\n* [GSDC - Vehicle Speed Estimation by Doppler Shift](https://www.kaggle.com/code/saitodevel01/gsdc-vehicle-speed-estimation-by-doppler-shift/notebook)\n* [GSDC - Improved Raw GNSS Baseline](https://www.kaggle.com/code/saitodevel01/gsdc-improved-raw-gnss-baseline/notebook)\n* [DSDC - Unified post-processing](https://www.kaggle.com/code/saitodevel01/dsdc-unified-post-processing/notebook)\n* [GSDC - Bias EDA](https://www.kaggle.com/code/saitodevel01/gsdc-bias-eda/notebook)\n* [GSDC - Bias Correction](https://www.kaggle.com/code/saitodevel01/gsdc-bias-correction/notebook)\n\nThe detailed solution approach can be seen in [this forum post](https://www.kaggle.com/c/google-smartphone-decimeter-challenge/discussion/261959)\n\nPlease share any additional interesting notebooks from the last competition in comments. Thank you.", "1775875": "A great roundup of helpful notebooks from the last GSDC competition! This is a great resource for anyone looking to get started in the competition.", "1811054": "Thank you for a very nice collection of notebooks.\nVery useful as I did not attend the last GSDC.", "1815614": "Thanks SRk for giving the overview to reach to the goals." }, "source": "meta" }