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69393429 | <kaggle_start><data_title>progresbar2-local<data_name>progresbar2local
<code># # The Bernstein Bears CRP Submission 1
# install necessary libraries from input
# import progressbar library for offline usage
# import text stat library for additional ml data prep
FAST_DEV_RUN = False
USE_CHECKPOINT = True
USE_HIDDEN_IN_RG... | /fsx/loubna/kaggle_data/kaggle-code-data/data/0069/393/69393429.ipynb | progresbar2local | justinchae | [{"Id": 69393429, "ScriptId": 18638229, "ParentScriptVersionId": NaN, "ScriptLanguageId": 9, "AuthorUserId": 4319244, "CreationDate": "07/30/2021 12:40:32", "VersionNumber": 36.0, "Title": "The Bernstein Bears CRP Submission 1", "EvaluationDate": "07/30/2021", "IsChange": true, "TotalLines": 887.0, "LinesInsertedFromPr... | [{"Id": 92503477, "KernelVersionId": 69393429, "SourceDatasetVersionId": 2311525}, {"Id": 92503478, "KernelVersionId": 69393429, "SourceDatasetVersionId": 2312589}, {"Id": 92503476, "KernelVersionId": 69393429, "SourceDatasetVersionId": 2311499}] | [{"Id": 2311525, "DatasetId": 1394642, "DatasourceVersionId": 2352908, "CreatorUserId": 4319244, "LicenseName": "Unknown", "CreationDate": "06/07/2021 14:51:02", "VersionNumber": 1.0, "Title": "progresbar2-local", "Slug": "progresbar2local", "Subtitle": "Downloaded for offline use in kaggle \"no internet\" kernels", "D... | [{"Id": 1394642, "CreatorUserId": 4319244, "OwnerUserId": 4319244.0, "OwnerOrganizationId": NaN, "CurrentDatasetVersionId": 2311525.0, "CurrentDatasourceVersionId": 2352908.0, "ForumId": 1413893, "Type": 2, "CreationDate": "06/07/2021 14:51:02", "LastActivityDate": "06/07/2021", "TotalViews": 934, "TotalDownloads": 4, ... | [{"Id": 4319244, "UserName": "justinchae", "DisplayName": "Justin Chae", "RegisterDate": "01/12/2020", "PerformanceTier": 1}] | # # The Bernstein Bears CRP Submission 1
# install necessary libraries from input
# import progressbar library for offline usage
# import text stat library for additional ml data prep
FAST_DEV_RUN = False
USE_CHECKPOINT = True
USE_HIDDEN_IN_RGR = False
N_FEATURES_TO_USE_HEAD = 1
N_FEATURES_TO_USE_TAIL = None
# in this ... | false | 0 | 9,748 | 0 | 27 | 9,748 | ||
69716135 | "<kaggle_start><data_title>ResNet-50<data_description># ResNet-50\n\n---\n\n## Deep Residual Learnin(...TRUNCATED) | /fsx/loubna/kaggle_data/kaggle-code-data/data/0069/716/69716135.ipynb | resnet50 | null | "[{\"Id\": 69716135, \"ScriptId\": 18933277, \"ParentScriptVersionId\": NaN, \"ScriptLanguageId\": 9(...TRUNCATED) | "[{\"Id\": 93188012, \"KernelVersionId\": 69716135, \"SourceDatasetVersionId\": 9900}, {\"Id\": 9318(...TRUNCATED) | "[{\"Id\": 9900, \"DatasetId\": 6209, \"DatasourceVersionId\": 9900, \"CreatorUserId\": 484516, \"Li(...TRUNCATED) | "[{\"Id\": 6209, \"CreatorUserId\": 484516, \"OwnerUserId\": NaN, \"OwnerOrganizationId\": 1202.0, \(...TRUNCATED) | null | "# # Title:Skin-Lesion Segmentation\n# ### Importing the Libraries\nfrom keras.models import Model, (...TRUNCATED) | false | 0 | 23,035 | 0 | 608 | 23,035 | ||
69293649 | "<kaggle_start><code># 生成data文件\nimport os\nfrom os.path import join, isfile\nimport numpy a(...TRUNCATED) | /fsx/loubna/kaggle_data/kaggle-code-data/data/0069/293/69293649.ipynb | null | null | "[{\"Id\": 69293649, \"ScriptId\": 18546956, \"ParentScriptVersionId\": NaN, \"ScriptLanguageId\": 9(...TRUNCATED) | null | null | null | null | "# 生成data文件\nimport os\nfrom os.path import join, isfile\nimport numpy as np\nimport h5py\nf(...TRUNCATED) | false | 0 | 19,374 | 0 | 6 | 19,374 | ||
69955597 | "<kaggle_start><code>from learntools.core import binder\n\nbinder.bind(globals())\nfrom learntools.p(...TRUNCATED) | /fsx/loubna/kaggle_data/kaggle-code-data/data/0069/955/69955597.ipynb | null | null | "[{\"Id\": 69955597, \"ScriptId\": 19129579, \"ParentScriptVersionId\": NaN, \"ScriptLanguageId\": 9(...TRUNCATED) | null | null | null | null | "from learntools.core import binder\n\nbinder.bind(globals())\nfrom learntools.python.ex7 import *\n(...TRUNCATED) | false | 0 | 2,582 | 0 | 6 | 2,582 | ||
69728033 | "<kaggle_start><data_title>mlb_unnested<data_description>ref: https://www.kaggle.com/naotaka1128/cre(...TRUNCATED) | /fsx/loubna/kaggle_data/kaggle-code-data/data/0069/728/69728033.ipynb | mlb-unnested | naotaka1128 | "[{\"Id\": 69728033, \"ScriptId\": 19051813, \"ParentScriptVersionId\": NaN, \"ScriptLanguageId\": 9(...TRUNCATED) | [{"Id": 93200478, "KernelVersionId": 69728033, "SourceDatasetVersionId": 2323733}] | "[{\"Id\": 2323733, \"DatasetId\": 1402611, \"DatasourceVersionId\": 2365235, \"CreatorUserId\": 164(...TRUNCATED) | "[{\"Id\": 1402611, \"CreatorUserId\": 164146, \"OwnerUserId\": 164146.0, \"OwnerOrganizationId\": N(...TRUNCATED) | "[{\"Id\": 164146, \"UserName\": \"naotaka1128\", \"DisplayName\": \"ML_Bear\", \"RegisterDate\": \"(...TRUNCATED) | "# ## About this notebook\n# + train on 2021 regular season data(use update data\n# + cv on may,2021(...TRUNCATED) | false | 1 | 15,688 | 2 | 56 | 15,688 | ||
87643680 | "<kaggle_start><data_title>OCTant project<data_name>octant-project\n<code># # Enhancing an open-sour(...TRUNCATED) | /fsx/loubna/kaggle_data/kaggle-code-data/data/0087/643/87643680.ipynb | octant-project | nwheeler443 | "[{\"Id\": 87643680, \"ScriptId\": 24617507, \"ParentScriptVersionId\": NaN, \"ScriptLanguageId\": 9(...TRUNCATED) | [{"Id": 117988798, "KernelVersionId": 87643680, "SourceDatasetVersionId": 3175055}] | "[{\"Id\": 3175055, \"DatasetId\": 1929287, \"DatasourceVersionId\": 3224540, \"CreatorUserId\": 359(...TRUNCATED) | "[{\"Id\": 1929287, \"CreatorUserId\": 359577, \"OwnerUserId\": 359577.0, \"OwnerOrganizationId\": N(...TRUNCATED) | "[{\"Id\": 359577, \"UserName\": \"nwheeler443\", \"DisplayName\": \"Nicole Wheeler\", \"RegisterDat(...TRUNCATED) | "# # Enhancing an open-source OCT segmentation tool with manual segmentation capabilities\n# ## Intr(...TRUNCATED) | false | 0 | 24,379 | 0 | 23 | 24,379 | ||
87084457 | "<kaggle_start><code># # Objective of first fast YOLO inspired network\n# The first network will gen(...TRUNCATED) | /fsx/loubna/kaggle_data/kaggle-code-data/data/0087/084/87084457.ipynb | null | null | "[{\"Id\": 87084457, \"ScriptId\": 24134606, \"ParentScriptVersionId\": NaN, \"ScriptLanguageId\": 9(...TRUNCATED) | null | null | null | null | "# # Objective of first fast YOLO inspired network\n# The first network will generate a square where(...TRUNCATED) | false | 0 | 3,597 | 0 | 6 | 3,597 | ||
87964295 | "<kaggle_start><code># !curl https://raw.githubusercontent.com/pytorch/xla/master/contrib/scripts/en(...TRUNCATED) | /fsx/loubna/kaggle_data/kaggle-code-data/data/0087/964/87964295.ipynb | null | null | "[{\"Id\": 87964295, \"ScriptId\": 24700958, \"ParentScriptVersionId\": NaN, \"ScriptLanguageId\": 9(...TRUNCATED) | null | null | null | null | "# !curl https://raw.githubusercontent.com/pytorch/xla/master/contrib/scripts/env-setup.py -o pytorc(...TRUNCATED) | false | 0 | 3,368 | 0 | 6 | 3,368 | ||
87597153 | "<kaggle_start><code># # HW2B: Neural Machine Translation\n# In this project, you will build a neura(...TRUNCATED) | /fsx/loubna/kaggle_data/kaggle-code-data/data/0087/597/87597153.ipynb | null | null | "[{\"Id\": 87597153, \"ScriptId\": 24604634, \"ParentScriptVersionId\": NaN, \"ScriptLanguageId\": 9(...TRUNCATED) | null | null | null | null | "# # HW2B: Neural Machine Translation\n# In this project, you will build a neural machine translatio(...TRUNCATED) | false | 0 | 8,157 | 0 | 6 | 8,157 | ||
87030978 | "<kaggle_start><code>import numpy as np # linear algebra\nimport pandas as pd # data processing, C(...TRUNCATED) | /fsx/loubna/kaggle_data/kaggle-code-data/data/0087/030/87030978.ipynb | null | null | "[{\"Id\": 87030978, \"ScriptId\": 23915017, \"ParentScriptVersionId\": NaN, \"ScriptLanguageId\": 9(...TRUNCATED) | null | null | null | null | "import numpy as np # linear algebra\nimport pandas as pd # data processing, CSV file I/O (e.g. pd(...TRUNCATED) | false | 0 | 5,933 | 0 | 6 | 5,933 |
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