I'm looking for a team. I am a DS in manufacturing. Math/Statistics/ OR background, working on DL for the last couple years. Living in SLC where Recursion is located. Owns DL dev box with 4 1080Ti. I'm wondering 6 channels CNN rather than 3 channels (maybe we have to forget about transfer learning, or maybe there's a trick? Not much benefits since they are highly independent channels? ). Disentangling is an interesting theme. Maybe an auto-encoder and deep representation helps? Interested in working on TFRecord, SavedModel, MirrorStrategy, or some of the Nvidia libraries in Nvidia GPU Cloud, or maybe we can try TPU.
\n\nThis is my 2nd kaggle. Looking forward to enjoy the competition with a team. Let me know if you are looking for a teammate.
", "messages": [ { "id": 572595, "postDate": "2019-07-11T06:37:24.043Z", "content": "Hi Mei,
\n\nIm a newbie at kaggle but I have done deep learning projects like flower classification and Attendance system with face recognition. Can I please join your team?
", "rawMarkdown": "Hi Mei,\n\nIm a newbie at kaggle but I have done deep learning projects like flower classification and Attendance system with face recognition. Can I please join your team?", "votes": 1 }, { "id": 571136, "postDate": "2019-07-09T07:58:46.660Z", "content": "Hello Mei,\nI have recently taken advanced Topological Data Analytics and I would love to team up and work on my 1st competition.
", "rawMarkdown": "Hello Mei,\nI have recently taken advanced Topological Data Analytics and I would love to team up and work on my 1st competition.", "votes": 1, "replies": [ { "id": 571391, "postDate": "2019-07-09T14:54:48.277Z", "content": "Tx Enzo, will contact you.
", "rawMarkdown": "Tx Enzo, will contact you." } ] }, { "id": 571043, "postDate": "2019-07-09T05:16:27.703Z", "content": "I'm looking for a team. I am a DS in manufacturing. Math/Statistics/ OR background, working on DL for the last couple years. Living in SLC where Recursion is located. Owns DL dev box with 4 1080Ti. I'm wondering 6 channels CNN rather than 3 channels (maybe we have to forget about transfer learning, or maybe there's a trick? Not much benefits since they are highly independent channels? ). Disentangling is an interesting theme. Maybe an auto-encoder and deep representation helps? Interested in working on TFRecord, SavedModel, MirrorStrategy, or some of the Nvidia libraries in Nvidia GPU Cloud, or maybe we can try TPU.
\n\nThis is my 2nd kaggle. Looking forward to enjoy the competition with a team. Let me know if you are looking for a teammate.
", "rawMarkdown": "I'm looking for a team. I am a DS in manufacturing. Math/Statistics/ OR background, working on DL for the last couple years. Living in SLC where Recursion is located. Owns DL dev box with 4 1080Ti. I'm wondering 6 channels CNN rather than 3 channels (maybe we have to forget about transfer learning, or maybe there's a trick? Not much benefits since they are highly independent channels? ). Disentangling is an interesting theme. Maybe an auto-encoder and deep representation helps? Interested in working on TFRecord, SavedModel, MirrorStrategy, or some of the Nvidia libraries in Nvidia GPU Cloud, or maybe we can try TPU.\n\nThis is my 2nd kaggle. Looking forward to enjoy the competition with a team. Let me know if you are looking for a teammate." }, { "id": 571889, "postDate": "2019-07-10T07:41:29.273Z", "rawMarkdown": "", "votes": 1, "isDeleted": true, "replies": [ { "id": 572526, "postDate": "2019-07-11T03:18:10.630Z", "content": "Hi Dani, great to hear from you. will follow up.
", "rawMarkdown": "Hi Dani, great to hear from you. will follow up." }, { "id": 572532, "postDate": "2019-07-11T03:24:59.673Z", "content": "Hi Dani, looks like I can not contact you. Can you try contacting me? or Can you try access here? https://kagglerecursionteamx.slack.com/messages/CL9MG0Q3A/team/UL97PKAJG/
", "rawMarkdown": "Hi Dani, looks like I can not contact you. Can you try contacting me? or Can you try access here? https://kagglerecursionteamx.slack.com/messages/CL9MG0Q3A/team/UL97PKAJG/\n" }, { "id": 572955, "postDate": "2019-07-11T15:41:34.293Z", "rawMarkdown": "", "votes": 1, "isDeleted": true } ] } ], "comments": [ { "id": 572595, "author_name": "", "author_url": "", "post_date": "2019-07-11T06:37:24.043000", "content": "Hi Mei,
\n\nIm a newbie at kaggle but I have done deep learning projects like flower classification and Attendance system with face recognition. Can I please join your team?
", "votes": 1, "replies": [] }, { "id": 571136, "author_name": "Enzo Rodriguez", "author_url": "", "post_date": "2019-07-09T07:58:46.660000", "content": "Hello Mei,\nI have recently taken advanced Topological Data Analytics and I would love to team up and work on my 1st competition.
", "votes": 1, "replies": [ { "id": 571391, "author_name": "Mei Todaka", "author_url": "", "post_date": "2019-07-09T14:54:48.277000", "content": "Tx Enzo, will contact you.
", "votes": 0, "replies": [] } ] }, { "id": 571889, "author_name": "", "author_url": "", "post_date": "2019-07-10T07:41:29.273000", "content": "", "votes": 1, "replies": [ { "id": 572526, "author_name": "Mei Todaka", "author_url": "", "post_date": "2019-07-11T03:18:10.630000", "content": "Hi Dani, great to hear from you. will follow up.
", "votes": 0, "replies": [] }, { "id": 572532, "author_name": "Mei Todaka", "author_url": "", "post_date": "2019-07-11T03:24:59.673000", "content": "Hi Dani, looks like I can not contact you. Can you try contacting me? or Can you try access here? https://kagglerecursionteamx.slack.com/messages/CL9MG0Q3A/team/UL97PKAJG/
", "votes": 0, "replies": [] }, { "id": 572955, "author_name": "", "author_url": "", "post_date": "2019-07-11T15:41:34.293000", "content": "", "votes": 1, "replies": [] } ] } ], "raw_markdown_by_id": { "572595": "Hi Mei,\n\nIm a newbie at kaggle but I have done deep learning projects like flower classification and Attendance system with face recognition. Can I please join your team?", "571136": "Hello Mei,\nI have recently taken advanced Topological Data Analytics and I would love to team up and work on my 1st competition.", "571043": "I'm looking for a team. I am a DS in manufacturing. Math/Statistics/ OR background, working on DL for the last couple years. Living in SLC where Recursion is located. Owns DL dev box with 4 1080Ti. I'm wondering 6 channels CNN rather than 3 channels (maybe we have to forget about transfer learning, or maybe there's a trick? Not much benefits since they are highly independent channels? ). Disentangling is an interesting theme. Maybe an auto-encoder and deep representation helps? Interested in working on TFRecord, SavedModel, MirrorStrategy, or some of the Nvidia libraries in Nvidia GPU Cloud, or maybe we can try TPU.\n\nThis is my 2nd kaggle. Looking forward to enjoy the competition with a team. Let me know if you are looking for a teammate.", "571889": "" } }