Machine Learning on Geographical Data Using Python
1ª edição
Ofertas
1 loja
Ano 2022·Páginas 330·Formato BOOK·ISBN 9781484282861
Sobre o livro
Chapter 1: Introduction to Geodata
Chapter 3: Geodata Data Types: Points, Lines, Polygons, Raster
Chapter Goal: Presenting what geodata is, how to represent it, its difficulties
No of pages 20
Sub -Topics
1. Geodata definitions
2. Geographical Information Systems and common tools
3. Standard formats of geographical data
4. Overview of Python tools for geodata
Chapter 2: Coordinate Systems and Projections
Chapter Goal: Introduce coordinate systems and projections
No of pages: 20
Sub - Topics 1. Geographical coordinates
2. Geographical coordinate systems
3. Map projections
4. Conversions between coordinate systems
Chapter Goal: Explain the four main data types in geodata
No of pages : 20
Sub - Topics:
1. Points
2. Lines
3. Polygons
4. Raster
Chapter 4: Creating Maps
Chapter Goal: Learn how to create maps in Python
No of pages : 20
Sub - Topics:
1. Discover mapping libraries
2. See how to create maps with different data types
Chapter 5: Basic Operations 1: Clipping and Intersecting in Python
Chapter Goal: Learn clipping and intersecting in Python
No of pages: 20
Sub - Topics:
1. What is clipping?
2. How to do clipping in Python?
3. What is intersecting
4. How to do intersecting in Python?
Chapter 6: Basic Operations 2: Buffering in Python
Chapter Goal: Learn how to create buffers in Python
No of pages: 20
Sub - Topics:
1. What are buffers?
2. How to create buffers in Python
Chapter 7: Basic Operations 3: Merge and Dissolve in Python
Chapter Goal: Learn how to merge and dissolve in Python
No of pages: 20Sub - Topics:
1. What is the merge operation?
2. How to do the merge operation in Python?
3. What is the dissolve operation?
4. How to do the dissolve operation in Python?
Chapter 8: Basic Operations 4: Erase in Python
Chapter Goal: Learn how to do an erase in Python
No of pages: 20
Sub - Topics:
1. What is the erase operation?
2. How to apply the erase operation in Python
Chapter 9: Machine Learning: Interpolation
Chapter Goal: Learn how to do interpolation Python
No of pages: 20
Sub - Topics:
1.What is interpolation?
2.How to do interpolation in Python
3.Different methods for spatial interpolation in PythonChapter 10: Machine Learning: Classification
Chapter Goal: Learn how to do classification on geodata in Python
No of pages: 20
Sub - Topics:
1.What is classification?
2.How to do classification on geodata in Python?
3.In depth example application of classification on geodata.
Chapter 11: Machine Learning: Regression
Chapter Goal: Learn how to do regression on geodata in Python
No of pages: 20
Sub - Topics:
1.What is regression?
2.How to do regression on geodata in Python?
3.In depth example application of regression on geodata.
Chapter 12: Machine Learning: Clustering
Chapter Goal: Learn how to do clustering on geodata in Python
No of pages: 20
Sub - Topics:
1.What is clustering?
2.How to do clustering on geodata in Python?
3.In depth example application of clustering on geodata.
Chapter
Ficha técnica
- Autor
- Korstanje, Joos, Joos Korstanje
- Editora
- UmLivro, Springer Nature BV (Print-On-Demand)
- Formato
- BOOK
- Encadernação
- Capa comum
- ISBN
- 9781484282861
- EAN
- 9781484282861
- Ano de Publicação
- 2022
- Número de Páginas
- 330
- Dimensões
- 25.4 x 17.8 x 3 cm
- Peso
- 0.58 kg
- Idioma
- pt-BR
- Edição
- 1
- SKU
- 9781484282861