![\"\"](\"https://media.giphy.com/media/KJ1f5iTl4Oo7u/giphy.gif\")
First off, I really want to thank everyone who participated in this competition! You are part of the biggest open creation of discussion topics, model and workflow examples, and value for the building energy performance analysis community in our history!
\n\nOur goal with this competition was to create a huge amount of ideas, tutorials and solutions to help steer the building science and data science communities closer together -- and I think it worked!
\n\nWe are in the process of curating a directory of Notebooks for building performance engineers and analysts from the competition that will serve as a recipe book for beginners as well as experts who are curious to learn about certain topics. We highly encourage you all to share your solutions as a notebook for this purpose.
\n\nWe will acknowledge the authors of all notebooks in this process, so please annotate your notebook or profile with how you would like to be acknowledged.
\n\nIt would also be helpful if you could indicate whether you are an ASHRAE member.
\n\nFinally, I just want to say thank you to all the participants who stuck out the competition despite the frustrations! The technical team worked really hard with the Kaggle team to get this competition up and running -- we knew there would be hiccups, but we also knew it would create value for the community regardless. If you continue to work on data from buildings in your career, you will quickly see the real-world challenges that I think we helped prepare you for :)
\n\n
First off, I really want to thank everyone who participated in this competition! You are part of the biggest open creation of discussion topics, model and workflow examples, and value for the building energy performance analysis community in our history!
\n\nOur goal with this competition was to create a huge amount of ideas, tutorials and solutions to help steer the building science and data science communities closer together -- and I think it worked!
\n\nWe are in the process of curating a directory of Notebooks for building performance engineers and analysts from the competition that will serve as a recipe book for beginners as well as experts who are curious to learn about certain topics. We highly encourage you all to share your solutions as a notebook for this purpose.
\n\nWe will acknowledge the authors of all notebooks in this process, so please annotate your notebook or profile with how you would like to be acknowledged.
\n\nIt would also be helpful if you could indicate whether you are an ASHRAE member.
\n\nFinally, I just want to say thank you to all the participants who stuck out the competition despite the frustrations! The technical team worked really hard with the Kaggle team to get this competition up and running -- we knew there would be hiccups, but we also knew it would create value for the community regardless. If you continue to work on data from buildings in your career, you will quickly see the real-world challenges that I think we helped prepare you for :)
\n\n
A very sincere thank you to all the contestants who have shared already! We really appreciate it.
", "rawMarkdown": "A very sincere thank you to all the contestants who have shared already! We really appreciate it.", "votes": null }, { "id": "717643", "postDate": "01/13/2020 12:06:38", "content": "I think you can use our solution as well. We still believe we could get gold if leaderboard wasn't manipulated. My side of the solution are already well-documented and shared. It will definitely help you.
\n\nEDA and Preprocessing (cleaning, feature engineering and etc.)\nhttps://www.kaggle.com/gunesevitan/ashrae-eda-and-preprocessing
\n\nLightGBM without leak\nhttps://www.kaggle.com/gunesevitan/ashrae-lightgbm-1-048-no-leak
", "rawMarkdown": "I think you can use our solution as well. We still believe we could get gold if leaderboard wasn't manipulated. My side of the solution are already well-documented and shared. It will definitely help you.\n\nEDA and Preprocessing (cleaning, feature engineering and etc.)\nhttps://www.kaggle.com/gunesevitan/ashrae-eda-and-preprocessing\n\nLightGBM without leak\nhttps://www.kaggle.com/gunesevitan/ashrae-lightgbm-1-048-no-leak", "votes": null }, { "id": "718010", "postDate": "01/13/2020 22:03:03", "content": "Here is my work on the competition Ashrae-III
", "rawMarkdown": "Here is my work on the competition [Ashrae-III](https://www.kaggle.com/sabinhashmi/ashrae-energy-prediction)", "votes": null } ], "comments": [ { "id": 717344, "author_name": "claytonmiller", "author_url": "", "post_date": "01/13/2020 03:35:35", "content": "A very sincere thank you to all the contestants who have shared already! We really appreciate it.
", "votes": null, "replies": [] }, { "id": 717643, "author_name": "mpwolke", "author_url": "", "post_date": "01/13/2020 12:06:38", "content": "I think you can use our solution as well. We still believe we could get gold if leaderboard wasn't manipulated. My side of the solution are already well-documented and shared. It will definitely help you.
\n\nEDA and Preprocessing (cleaning, feature engineering and etc.)\nhttps://www.kaggle.com/gunesevitan/ashrae-eda-and-preprocessing
\n\nLightGBM without leak\nhttps://www.kaggle.com/gunesevitan/ashrae-lightgbm-1-048-no-leak
", "votes": null, "replies": [] }, { "id": 718010, "author_name": "sabinhashmi", "author_url": "", "post_date": "01/13/2020 22:03:03", "content": "Here is my work on the competition Ashrae-III
", "votes": null, "replies": [] } ], "raw_markdown_by_id": { "717279": "First off, I really want to thank everyone who participated in this competition! You are part of the biggest open creation of discussion topics, model and workflow examples, and value for the building energy performance analysis community in our history! \n\nOur goal with this competition was to create a huge amount of ideas, tutorials and solutions to help steer the building science and data science communities closer together -- and I think it worked!\n\nWe are in the process of curating a directory of Notebooks for building performance engineers and analysts from the competition that will serve as a *recipe book* for beginners as well as experts who are curious to learn about certain topics. **We highly encourage you all to share your solutions as a notebook** for this purpose. \n\nWe will acknowledge the authors of all notebooks in this process, so please annotate your notebook or profile with how you would like to be acknowledged. \n\n*It would also be helpful if you could indicate whether you are an ASHRAE member.*\n\nFinally, I just want to say thank you to all the participants who stuck out the competition despite the frustrations! The technical team worked really hard with the Kaggle team to get this competition up and running -- *we knew there would be hiccups, but we also knew it would create value for the community regardless*. If you continue to work on data from buildings in your career, you will quickly see the real-world challenges that I think we helped prepare you for :)\n\n", "717344": "A very sincere thank you to all the contestants who have shared already! We really appreciate it.", "717643": "", "717846": "I think you can use our solution as well. We still believe we could get gold if leaderboard wasn't manipulated. My side of the solution are already well-documented and shared. It will definitely help you.\n\nEDA and Preprocessing (cleaning, feature engineering and etc.)\nhttps://www.kaggle.com/gunesevitan/ashrae-eda-and-preprocessing\n\nLightGBM without leak\nhttps://www.kaggle.com/gunesevitan/ashrae-lightgbm-1-048-no-leak", "718010": "Here is my work on the competition [Ashrae-III](https://www.kaggle.com/sabinhashmi/ashrae-energy-prediction)" }, "source": "meta" }