Machine Learning for Predictive Maps in Python and Leaflet
Machine Learning for Predictive Maps in Python and Leaflet, available at $59.99, has an average rating of 4.75, with 32 lectures, based on 69 reviews, and has 3316 subscribers.
You will learn about Web Mapping Data Transformation and Manipulation Python and GeoDjango Geospatial Machine Learning Data Mapping and Visualization Web GIS Programming This course is ideal for individuals who are Python Developers at any level or GIS Developers at any level or Developers at any level or Machine Learning engineers at any level or The curious mind It is particularly useful for Python Developers at any level or GIS Developers at any level or Developers at any level or Machine Learning engineers at any level or The curious mind.
Enroll now: Machine Learning for Predictive Maps in Python and Leaflet
Summary
Title: Machine Learning for Predictive Maps in Python and Leaflet
Price: $59.99
Average Rating: 4.75
Number of Lectures: 32
Number of Published Lectures: 32
Number of Curriculum Items: 32
Number of Published Curriculum Objects: 32
Original Price: R849.99
Quality Status: approved
Status: Live
What You Will Learn
- Web Mapping
- Data Transformation and Manipulation
- Python and GeoDjango
- Geospatial Machine Learning
- Data Mapping and Visualization
- Web GIS Programming
Who Should Attend
- Python Developers at any level
- GIS Developers at any level
- Developers at any level
- Machine Learning engineers at any level
- The curious mind
Target Audiences
- Python Developers at any level
- GIS Developers at any level
- Developers at any level
- Machine Learning engineers at any level
- The curious mind
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.
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You will learn how to build a full stack web gis application
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You will learn how to build predictive models
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You will learn how to build a prediction engine that’s embedded in the application
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You will learn how to build and automate a machine learning pipeline
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You will learn how to use multiple basesmaps and layers
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You will learn programming in leaflet.js
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You will learn how to create REST API endpoints and call them with Ajax and JQUERY
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You will learn how to use the Django template engine to pass data from the back-end to the front-end of the application
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You will learn how to integrate a PostgreSQL database with Django
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You will also learn how to visualize data on a map
Course Curriculum
Chapter 1: Introduction
Lecture 1: Introduction
Chapter 2: Setup and Installations
Lecture 1: Python Installation
Lecture 2: Creating a Python Virtual Environment
Lecture 3: Installing Django
Lecture 4: Installing Visual Studio Code IDE
Lecture 5: Installing PostgreSQL Database Server Part 1
Lecture 6: Installing PostgreSQL Database Server Part 2
Chapter 3: Writing the Django Server-Side Code
Lecture 1: Adding the settings.py Code
Lecture 2: Creating a Django Model
Lecture 3: Adding the admin.py Code
Chapter 4: Writing the Application Front-end Code
Lecture 1: Creating Template Files
Lecture 2: Creating Django Views
Lecture 3: Creating URL Patterns for the REST API
Lecture 4: Adding the index.html code
Lecture 5: Adding the layout.html code
Lecture 6: Creating our First Map
Lecture 7: Adding Markers
Chapter 5: Machine Learning
Lecture 1: Installing Jupyter Notebook
Lecture 2: Data Pre-processing
Lecture 3: Model Selection
Lecture 4: Model Evaluation and Building a Prediction Dataset
Chapter 6: Automating the Machine Learning Pipeline
Lecture 1: Creating a Django Model
Lecture 2: Embedding the Machine Learning Pipeline in the Application
Lecture 3: Creating a URL Endpoint for our Prediction Dataset
Chapter 7: Leaflet Programming
Lecture 1: Creating Multiple Basemaps
Lecture 2: Creating the Marker Layer Group
Lecture 3: Creating the Point Layer Group
Lecture 4: Creating the Predicted Point Layer Group
Lecture 5: Creating the Predicted High Risk Point Layer Group
Lecture 6: Creating the Legend
Lecture 7: Creating the Prediction Score Legend
Chapter 8: Project Source Code
Lecture 1: Source Code and Notebook
Instructors
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EBISYS R&D
Big Data Engineering
Rating Distribution
- 1 stars: 2 votes
- 2 stars: 5 votes
- 3 stars: 7 votes
- 4 stars: 19 votes
- 5 stars: 36 votes
Frequently Asked Questions
How long do I have access to the course materials?
You can view and review the lecture materials indefinitely, like an on-demand channel.
Can I take my courses with me wherever I go?
Definitely! If you have an internet connection, courses on Udemy are available on any device at any time. If you don’t have an internet connection, some instructors also let their students download course lectures. That’s up to the instructor though, so make sure you get on their good side!
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