[ WebToolTip.com ] Udemy - Geospatial Ai - Deep Learning For Satellite Imagery
[ WebToolTip.com ] Udemy - Geospatial Ai - Deep Learning For Satellite Imagery metadata, size 3272.15 MB, 119 files, category video, indexed at 2026-05-26.
资源标识
Infohashb35d042d2debd37904a94c92a8b1480355db80b7
总大小3.2 GB
格式mkv
分类视频
文件数119
发掘时间（北京时间）2026-05-26 22:16:29
最后活跃（北京时间）2026-05-26 22:17:24
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文件列表
| 文件名 | 格式 | 大小 |
|---|---|---|
| Get Bonus Downloads Here.url | url | 180 B |
| 1 - Welcome and Course Overview.html | html | 6.0 KB |
| 2 - Introduction to Geospatial Analysis.mkv | mkv | 127.2 MB |
| 3 - Introduction to Artificial Intelligence.mkv | mkv | 17.7 MB |
| 4 - Why Python is the Top Choice for AI.mkv | mkv | 13.8 MB |
| 5 - Overview of Deep Learning in Geospatial Applications.mkv | mkv | 124.2 MB |
| 6 - StepbyStep Guide to GPU Setup.mkv | mkv | 172.7 MB |
| 10 - Running PyTorch Models in the Cloud.mkv | mkv | 61.0 MB |
| 11 - Saving and Sharing Colab Notebooks.mkv | mkv | 78.4 MB |
| 7 - Introduction to Goggle Colab.mkv | mkv | 36.9 MB |
| 8 - Setting Up Google Colab for AI Projects.mkv | mkv | 78.5 MB |
| 9 - Running TensorFlow Models in the Cloud.mkv | mkv | 83.9 MB |
| 12 - Calculating Geospatial Indices.mkv | mkv | 104.8 MB |
| 13 - Import and Clean Datasets in Jupyter Notebook with Pandas.mkv | mkv | 129.9 MB |
| 14 - Calculate-zonal-statistics-1.ipynb | ipynb | 5.9 KB |
| 14 - Chirps-Erbil.tif | tif | 9.0 KB |
| 14 - Conducting Zonal Statistics in Python.mkv | mkv | 53.4 MB |
| 15 - Image-Preprocessing-for-Deep-Learning.ipynb | ipynb | 6.3 KB |
| 15 - Preprocessing Real Sentinel2 Imagery for Deep Learning.mkv | mkv | 113.7 MB |
| 16 - Integrating Google Earth Engine for Data Pipelines.mkv | mkv | 71.5 MB |
| 16 - Integrating-Google-Earth-Engine-for-Data-Pipelines.ipynb | ipynb | 5.0 KB |
| 17 - Working with LargeScale Geospatial Data.mkv | mkv | 134.7 MB |
| 17 - Working-with-Large-Scale-Geospatial-Data.ipynb | ipynb | 8.0 KB |
| Center_Erbil.cpg | cpg | 5 B |
| Center_Erbil.dbf | dbf | 1.7 KB |
| Center_Erbil.prj | prj | 145 B |
| Center_Erbil.sbn | sbn | 132 B |
| Center_Erbil.sbx | sbx | 116 B |
| Center_Erbil.shp | shp | 3.5 KB |
| Center_Erbil.shp.DESKTOP-U07KOO1.15896.13176.sr.lock | lock | 0 B |
| Center_Erbil.shx | shx | 108 B |
| Erbil_Admi_3.cpg | cpg | 5 B |
| Erbil_Admi_3.dbf | dbf | 20.5 KB |
| Erbil_Admi_3.ebb | ebb | 872 B |
| Erbil_Admi_3.ed1 | ed1 | 24.0 KB |
| Erbil_Admi_3.eq1 | eq1 | 208 B |
| Erbil_Admi_3.prj | prj | 143 B |
| Erbil_Admi_3.qpj | qpj | 257 B |
| Erbil_Admi_3.qtr | qtr | 136 B |
| Erbil_Admi_3.sbn | sbn | 324 B |
| Erbil_Admi_3.sbx | sbx | 132 B |
| Erbil_Admi_3.shp | shp | 41.9 KB |
| Erbil_Admi_3.shx | shx | 268 B |
| 18 - Introduction to CNNs for Satellite Imagery Analysis.mkv | mkv | 150.7 MB |
| 19 - Crop-Health-Using-RS-data-and-Neural-Networks.ipynb | ipynb | 67.2 KB |
| 19 - Designing a CNN Model for Crop Health Classification.mkv | mkv | 124.8 MB |
| 20 - Visualizing AI Model Performance.mkv | mkv | 178.0 MB |
| 20 - Visualizing-ML-Model-Performance.ipynb | ipynb | 69.5 KB |
| 20 - crop-health.csv | csv | 32.8 KB |
| 21 - Evaluating models Accuracy precision recall and crossvalidation.mkv | mkv | 48.9 MB |
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