I am new to Kaggle and data science and slowly working through this problem. I was able to download the zip file using the Kaggle API. However, I don't have enough memory to unzip it. Are there other methods to unzip these large datasets or is it a matter of buying an external hard drive? Thanks for helping a new person!
", "messages": [ { "id": 1196637, "postDate": "2021-02-11T14:18:53.490Z", "content": "You might need to check below discussions
\nhttps://www.kaggle.com/c/vinbigdata-chest-xray-abnormalities-detection/discussion/207824
\nhttps://www.kaggle.com/c/vinbigdata-chest-xray-abnormalities-detection/discussion/207955
\nhttps://www.kaggle.com/c/vinbigdata-chest-xray-abnormalities-detection/discussion/207859
\nhttps://www.kaggle.com/c/vinbigdata-chest-xray-abnormalities-detection/discussion/207823
Great people built downsampled jpg or png images from dicom, or you can check their code
", "rawMarkdown": "You might need to check below discussions\n\nhttps://www.kaggle.com/c/vinbigdata-chest-xray-abnormalities-detection/discussion/207824\nhttps://www.kaggle.com/c/vinbigdata-chest-xray-abnormalities-detection/discussion/207955\nhttps://www.kaggle.com/c/vinbigdata-chest-xray-abnormalities-detection/discussion/207859\nhttps://www.kaggle.com/c/vinbigdata-chest-xray-abnormalities-detection/discussion/207823\n\nGreat people built downsampled jpg or png images from dicom, or you can check their code", "votes": 2, "replies": [ { "id": 1196721, "postDate": "2021-02-11T15:35:33.613Z", "content": "Thank you! I also just figured out I could just use notebooks within Kaggle with the data already accessible and not what I have on my desktop.
", "rawMarkdown": "Thank you! I also just figured out I could just use notebooks within Kaggle with the data already accessible and not what I have on my desktop. ", "votes": 2 }, { "id": 1196916, "postDate": "2021-02-11T18:50:45.387Z", "content": "Hey @bakerbecker , There are multiple options, first is of course through Kaggle notebooks which is easier. However if you run out of GPU/TPU time on Kaggle, you can upload data on Google drive and use through Google colabs as well. Since only output csv file is required here, that should work fine. Happy Kaggling and all the best!
", "rawMarkdown": "Hey @bakerbecker , There are multiple options, first is of course through Kaggle notebooks which is easier. However if you run out of GPU/TPU time on Kaggle, you can upload data on Google drive and use through Google colabs as well. Since only output csv file is required here, that should work fine. Happy Kaggling and all the best!", "votes": 1 } ] }, { "id": 1196600, "postDate": "2021-02-11T13:54:36.293Z", "content": "I am new to Kaggle and data science and slowly working through this problem. I was able to download the zip file using the Kaggle API. However, I don't have enough memory to unzip it. Are there other methods to unzip these large datasets or is it a matter of buying an external hard drive? Thanks for helping a new person!
", "rawMarkdown": "I am new to Kaggle and data science and slowly working through this problem. I was able to download the zip file using the Kaggle API. However, I don't have enough memory to unzip it. Are there other methods to unzip these large datasets or is it a matter of buying an external hard drive? Thanks for helping a new person!", "votes": 2 }, { "id": 1211796, "postDate": "2021-02-20T15:10:27.447Z", "content": "Viel Glück ;)
", "rawMarkdown": "Viel Glück ;)" }, { "id": 1204736, "postDate": "2021-02-16T10:09:09.753Z", "content": "If it helps, you can follow these steps to download the dataset to Google Drive (and then access it via Colab):
\nhttps://www.kaggle.com/reubenschmidt/how-to-use-google-colab-for-extra-tpu-gpu
Hey Baker_Becker, I am also a beginner trying to tackle this problem. We are all going to make it. Just work it through step by step and use the amazing Kaggle community whenever you are stuck ! Good luck 💪
", "rawMarkdown": "Hey Baker_Becker, I am also a beginner trying to tackle this problem. We are all going to make it. Just work it through step by step and use the amazing Kaggle community whenever you are stuck ! Good luck 💪" } ], "comments": [ { "id": 1196637, "author_name": "JIN", "author_url": "", "post_date": "2021-02-11T14:18:53.490000", "content": "You might need to check below discussions
\nhttps://www.kaggle.com/c/vinbigdata-chest-xray-abnormalities-detection/discussion/207824
\nhttps://www.kaggle.com/c/vinbigdata-chest-xray-abnormalities-detection/discussion/207955
\nhttps://www.kaggle.com/c/vinbigdata-chest-xray-abnormalities-detection/discussion/207859
\nhttps://www.kaggle.com/c/vinbigdata-chest-xray-abnormalities-detection/discussion/207823
Great people built downsampled jpg or png images from dicom, or you can check their code
", "votes": 2, "replies": [ { "id": 1196721, "author_name": "Baker_Becker", "author_url": "", "post_date": "2021-02-11T15:35:33.613000", "content": "Thank you! I also just figured out I could just use notebooks within Kaggle with the data already accessible and not what I have on my desktop.
", "votes": 2, "replies": [] }, { "id": 1196916, "author_name": "Old Monk", "author_url": "", "post_date": "2021-02-11T18:50:45.387000", "content": "Hey @bakerbecker , There are multiple options, first is of course through Kaggle notebooks which is easier. However if you run out of GPU/TPU time on Kaggle, you can upload data on Google drive and use through Google colabs as well. Since only output csv file is required here, that should work fine. Happy Kaggling and all the best!
", "votes": 1, "replies": [] } ] }, { "id": 1211796, "author_name": "dr. Konya", "author_url": "", "post_date": "2021-02-20T15:10:27.447000", "content": "Viel Glück ;)
", "votes": 0, "replies": [] }, { "id": 1204736, "author_name": "Reuben Schmidt", "author_url": "", "post_date": "2021-02-16T10:09:09.753000", "content": "If it helps, you can follow these steps to download the dataset to Google Drive (and then access it via Colab):
\nhttps://www.kaggle.com/reubenschmidt/how-to-use-google-colab-for-extra-tpu-gpu
Hey Baker_Becker, I am also a beginner trying to tackle this problem. We are all going to make it. Just work it through step by step and use the amazing Kaggle community whenever you are stuck ! Good luck 💪
", "votes": 0, "replies": [] } ], "raw_markdown_by_id": { "1196637": "You might need to check below discussions\n\nhttps://www.kaggle.com/c/vinbigdata-chest-xray-abnormalities-detection/discussion/207824\nhttps://www.kaggle.com/c/vinbigdata-chest-xray-abnormalities-detection/discussion/207955\nhttps://www.kaggle.com/c/vinbigdata-chest-xray-abnormalities-detection/discussion/207859\nhttps://www.kaggle.com/c/vinbigdata-chest-xray-abnormalities-detection/discussion/207823\n\nGreat people built downsampled jpg or png images from dicom, or you can check their code", "1196600": "I am new to Kaggle and data science and slowly working through this problem. I was able to download the zip file using the Kaggle API. However, I don't have enough memory to unzip it. Are there other methods to unzip these large datasets or is it a matter of buying an external hard drive? Thanks for helping a new person!", "1211796": "Viel Glück ;)", "1204736": "If it helps, you can follow these steps to download the dataset to Google Drive (and then access it via Colab): \nhttps://www.kaggle.com/reubenschmidt/how-to-use-google-colab-for-extra-tpu-gpu", "1197971": "Hey Baker_Becker, I am also a beginner trying to tackle this problem. We are all going to make it. Just work it through step by step and use the amazing Kaggle community whenever you are stuck ! Good luck 💪" } }