Machine Learning for Predictive Maps in Python and Leaflet
What you'll learn
- Web Mapping
- Data Transformation and Manipulation
- Python and GeoDjango
- Geospatial Machine Learning
- Data Mapping and Visualization
- Web GIS Programming
- Basic Understanding of Python
- Little or no understanding of GIS
- Basic understanding of Programming concepts
- Basic understanding of Data
- Basic understanding of what Machine Learning is
Welcome to the Machine Learning for Predictive Maps in Python and Leaflet course.
In this course we will be building a earthquake forecasting map application,
by using a variety of independent tools and then integrate them to produce a full stack web gis application.
We will be writing code in multiple programming languages, which gives us experience
with different stacks of an application and different tools.
We will be covering various topics ranging from web gis, python programming, data analysis,
machine learning and geo data visualization. All of our development will be done on windows 10.
You will learn how to build a full stack web gis application
You will learn how to build predictive models
You will learn how to build a prediction engine that's embedded in the application
You will learn how to build and automate a machine learning pipeline
You will learn how to use multiple basesmaps and layers
You will learn programming in leaflet.js
You will learn how to create REST API endpoints and call them with Ajax and JQUERY
You will learn how to use the Django template engine to pass data from the back-end to the front-end of the application
You will learn how to integrate a PostgreSQL database with Django
You will also learn how to visualize data on a map
Who this course is for:
- Python Developers at any level
- GIS Developers at any level
- Developers at any level
- Machine Learning engineers at any level
- The curious mind
Big Data Engineering and Consulting, involved in multiple projects ranging from Business Intelligence, Software Engineering, IoT and Big data analytics. Expertise are in building data processing pipelines in the Hadoop and Cloud ecosystems and software development.
Currently consulting at one of the top business intelligence consultancies helping clients build data warehouses, data lakes, cloud data processing pipelines and machine learning pipelines. The technologies he uses to accomplish client requirements range from Hadoop, Amazon S3, Python, Django, Apache Spark, MSBI, Microsoft Azure, SQL Server Data Tools, Talend and Elastic MapReduce.