Machine Learning with Earth Engine Python and Colab

[mitsumi]

MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz
Language: English | Size: 348 MB | Duration: 39m

What you'll learn
Create training data for supervised classification
Import Landsat data
Remove clouds from satellite data
Run supervised classification algorithm
Calculate accuracy assessment
Download land cover classification

Requirements
This course has no requirements.
Description
Welcome to the Machine Learning with Earth Engine Python and Colab course.

This Earth Engine course is without a doubt the most comprehensive course for anyone who wants to apply machine learning in python using satellite data. Even if you have zero programming experience, this course will take you from beginner to mastery.

Here's why:

The course is taught by an experienced spatial data scientist and former NASA fellow.

The course has been updated to be 2021 ready and you'll be learning the latest tools available on the cloud.

We've taught over 16,000 students how to code and apply spatial data science and cloud computing.

You will have access to example data and sample scripts.

In this course we will cover the following topics:

Introduction to Earth Engine Python API

Sign Up with Earth Engine

Create training data for supervised classification

Import Landsat data

Remove clouds from satellite data

Run supervised classification (machine learning) algorithm

Calculate accuracy assessment

Download land cover classification data

The course includes HD video tutorials. We'll take you step-by-step through engaging video tutorials and teach you everything you need to know to apply remote sensing and cloud computing for forest monitoring application.

So, what are you waiting for? Click the buy now button and join the course.

Who this course is for:
Anyone who wants to learn cloud computing, machine learning and python using remote sensing data.

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