Data augmentation and loss function | DL

0:00 Intro
0:35 Overview the required things
2:50 Data augmentation (random rotation, flip and transform)
5:52 Shuffle dataset
6:25 Test imagery tiles
7:30 Unet model training
8:00 Callback functions (EarlyStopping and CheckPointer)
12:08 Prediction on tiles
----------------------------------------------------------------------------------------
Here are some playlists that you might be interested in:
----------------------------------------------------------------------------------------
1. Leaflet from basic to advance: • Leaflet from basic to ...
2. GeoServer with leaflet web-GIS: • GeoServer and Leaflet ...
3. GeoDjango project: • Bookmark note on map |...
4. geoserver-rest: • geoserver-rest
5. GIS training in Nepali: • Beginner GIS training ...
6. LULC map production: • LandUse Land Cover Map...
7. Geospatial analysis with python: • GeoSpatial analysis wi...
8. GeoNode from basic to advance: • GeoNode from basic to ...
9. Machine learning from the basic: • Machine Learning for g...
--------------------------------------------------------------------------------------------------------------
Check out my discounted courses at the following link:
--------------------------------------------------------------------------------------------------------------
1. "Geospatial data analysis with python": www.udemy.com/course/geospati...
2. "Web GIS Development 2021": www.udemy.com/course/web-gis-...
3. "Web mapping and Web-GIS from Dev to Deploy 2021: GeoDjango": www.udemy.com/course/web-mapp...
4. "Introduction to Web Mapping and Web GIS 2020: GeoDjango": www.udemy.com/course/introduc...
5. Deep Learning Application for Earth Observation: www.udemy.com/course/deep-lea...
6. Geospatial Data Analysis with Python: www.udemy.com/course/geospati...
---------------------------------------------------------------------------------------------------
Follow me on GitHub: github.com/iamtekson
Follow me on Twitter: / iamtekson
Follow me on Instagram: / iamtekson
Join Facebook group: / 1049524025731229
-----------------------------------------------------------------------------------------------------