Offered By: IBM

Data Science in Agriculture. Land use classification

In this lab, we will learn the basic methods of images transformation classification.

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GPXX0KHHEN

Data Science

1.08k+ Enrolled
(95)

At a Glance

In this lab, we will learn the basic methods of images transformation classification.

About

 In this laboratory, we will explore how land use types can be classified based on aerial and satellite photographs of the earth's surface. We will learn to build our own photo masks based on ready-made masks and display them on the screen, we will learn how to upload photos, transform pixels and colors into a data set. Then we will learn how to build a classifier and predict land use masks based on it.

In this lab, we will learn the basic methods of images transformation classification. The laboratory consists of four stages:
  • Download and visualization of images
  • DataSet creation
  • Classification model creation
  • Create your own mask of land use

After completing this lab, you will be able to:

  • Download and transform images.
  • Create a DataSet of the colors of images.
  • Build a classification model.
  • Build land use masks based on a classifier.
 

Estimated Effort

1 hour

Level

Advanced

Industries

Agriculture

Skills You Will Learn

Data Science

Language

English

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Instructors

Profile picture for Yaroslav Vyklyuk

Yaroslav Vyklyuk

Full Professor, Doctor of Computer Science, PhD

Dr. Yaroslav Vyklyuk is a full professor at the Lviv Polytechnic National University, Department of Artificial Intelligence Systems. He is an author of over 210 scientific works, 10 monographs, and books, a member of the Editorial Board of 6 international scientific journals, member of the Academic Councils on protection Ph.D. and DrSc thesis in "Mathematical modeling and computational methods". Research Interests: Data Science, Applied System Analysis, Mathematical Modeling, and Decision Making of Complex Dynamic Systems (socio-economic, geographical, tourist, and crisis systems) using Artificial Intelligence Technology, DataMining, Big Data, Parallel Calculations, Statistics, Econometrics, Econophysics and other Advanced Mathematical Methods with implementation into information, WEB, and geographic information systems.

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