Machine Learning in GIS : Understand the Theory and Practice

Understand & apply machine learning in Geographic information systems and Remote Sensing in QGIS and Google Earth Engine

This course is designed to equip you with the theoretical and practical knowledge of Machine Learning as applied for geospatial analysis, namely Geographic Information Systems (GIS) and Remote Sensing. By the end of the course, you will feel confident and completely understand the Machine Learning applications in GIS technology and how to use Machine Learning algorithms for various geospatial tasks, such as land use and land cover mapping (classifications) and object-based image analysis (segmentation). This course will also prepare you for using GIS with open source and free software tools.

In the course, you will be able to apply such Machine Learning algorithms as Random Forest, Support Vector Machines and Decision Trees (and others) for classification of satellite imagery. On top of that, you will practice GIS by completing an entire GIS project by exploring the power of Machine Learning, cloud computing and Big Data analysis using Google Erath Engine for any geographic area in the world.

The course is ideal for professionals such as geographers, programmers, social scientists, geologists, and all other experts who need to use maps in their field and would like to learn more about Machine Learning in GIS. If you’re planning to undertake a task that requires to use a state of the art Machine Learning algorithms for creating, for instance, land cover and land use maps, this course will give you the confidence you need to understand and solve such geospatial problem.

One important part of the course is the practical exercises. You will be given some precise instructions and datasets to create maps based on Machine Learning algorithms using the QGIS software and Google Earth Engine.

In this course, I include downloadable practical materials that will teach you:

– How to install open source GIS (QGIS, OTB toolbox) software on your computer and correctly configure it

– QGIS software interface including its main components and plug-ins

– Learn how to classify satellite images with different machine learning algorithms (random forest, support vector machines, decision trees and so on) in QGIS

– Learn how to perform image segmentation in QGIS

– Learn how to prepare your first land cover map using the cloud computing Google Earth Engine Platform.

Machine Learning in GIS : Understand the Theory and Practice

Understand & apply machine learning in Geographic information systems and Remote Sensing in QGIS and Google Earth Engine»

¿Te gustaron los cupones? Tal vez también te guste este otro contenido:

---

Este curso se encuentra de manera gratuita gracias a un cupón que podrás encontrar aquí abajo.

Toma en cuenta que este tipo de cupones duran por muy poco tiempo.

Si el cupón ya ha expirado podrás adquirir el curso de manera habitual.

Este tipo de cupones duran muy pocas horas, e incluso solo minutos después de haber sido publicados.

Debido a una actualización de Udemy ahora solo existen 1,000 cupones disponibles, NO nos hacemos responsables si el cupón ya venció.

Para obtener el curso con su cupón usa este enlace.