: 
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English + srt | Duration: 32 lectures (5h 58m) | Size: 2.1 GB
Using the power of machine learning to build predictive map applications
What you'll learn:
Web Mapping
Data Transformation and Manipulation
Python and GeoDjango
Geospatial Machine Learning
Data Mapping and Visualization
Web GIS Programming
Requirements
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
Description
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
Homepage
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