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.

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

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

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!