ML algorithms development for land cover mapping (0-100)

LULC mapping based on the advanced machine learning algorithms using QGIS, the Google Earth Engine, and Google Colab
4.32 (11 reviews)
Udemy
platform
English
language
Other
category
instructor
ML algorithms development for land cover mapping (0-100)
66
students
2 hours
content
Jan 2023
last update
$54.99
regular price

What you will learn

The concepts of Remote Sensing

How to collect satellite Images utilizing the Google Earth Engine (GEE)

How to create Reference/Ground truth data in QGIS (vector format)

How to convert reference data from vector data into raster data in QGIS

The concepts of machine learning algorithms

Read and import your data from your Google Drive into Google Colab

Develop different machine learning algorithms in Google Colab

Map Land use land covers in your region utilizing different machine learning algorithms

How to validate a machine-learning algorithm

How to model feature importance using tree-based algorithms

To create map layouts in QGIS

Screenshots

ML algorithms development for land cover mapping (0-100) - Screenshot_01ML algorithms development for land cover mapping (0-100) - Screenshot_02ML algorithms development for land cover mapping (0-100) - Screenshot_03ML algorithms development for land cover mapping (0-100) - Screenshot_04
5120628
udemy ID
1/29/2023
course created date
2/6/2023
course indexed date
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