Description
Spatial Machine Learning and Statistics in Python. This course provides a practical introduction to spatial machine learning and statistics using Python. Led by international expert Milan Januso, participants will be introduced to key concepts, challenges, and real-world applications in the field. The course begins by teaching the basics of spatial statistics, such as autocorrelation and spatial interpolation, using libraries such as GeoPandas. It then moves on to unsupervised machine learning techniques, including hotspot analysis, K-Means clustering, and DBSCAN, and applies these methods to geospatial data. The next section explores supervised learning methods, such as spatial feature engineering, regression models, and spatial random forests for predictive analytics. This course provides a solid foundation for further exploration in this field by equipping you with the skills to perform advanced statistical analysis and implement machine learning projects on spatial data.
What you will learn
- Fundamentals of Spatial Statistics: Learn the basics of autocorrelation and spatial interpolation.
- Spatial data analysis: Familiarity with hotspot analysis and clustering algorithms such as DBSCAN and K-Means.
- Supervised machine learning: Using regression and random forest models to make predictions on spatial data.
- Practical applications: Performing advanced statistical analyses and running machine learning tasks on spatial data.
This course is suitable for people who:
- Students and researchers in the fields of data science, geography, and spatial analysis.
- Machine learning engineers and data scientists looking to expand their skills to spatial data.
- Anyone interested in analyzing geographic data and using Python tools in this field.
Spatial Machine Learning and Statistics in Python course details
- Publisher: LinkedIn
- Instructor: Milan Janosov, Ph.D.
- Training level: Advanced
- Training duration: 1 hour and 18 minutes
Course headings
Course images
Sample course video
Installation Guide
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Subtitles: English
Quality: 720p
Download link
File(s) password: www.downloadly.ir
File size
136 MB