Name: Machine Learning for Predictive Maps in Python and Leaflet
Price: 30.00 GBP

Machine Learning for Predictive Maps in Python and Leaflet

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Machine Learning for Predictive Maps in Python and Leaflet

Learn how to multi-skill in programming and make a full stack web GIS application by taking this course on Machine Learning for Predictive Maps in Python and Leaflet. This comprehensive training will show you how to use the available tools and write code on the most widely-used programming language to make powerful forecasting applications.

This innovative Python tutorial provides an ideal way to learn how to use these versatile functions and essential technology to create unique and useful projects. To achieve this, you will be taught how to set up a predictive environment, write Django server-side code, enable machine learning capabilities, and perform intricate leaflet programming. The final results of the assigned project will allow you to produce even more impressive forecasting routines for all manner of uses.

When you complete this training, you will have mastered the fundamental skills and knowledge of machine learning on the most popular platforms, raising your IT profile to a greater level for employment and personal projects.

Imperial Academy offers this premium Machine Learning for Predictive Maps in Python and Leaflet course to ensure security in your career. In addition, this comprehensive Machine Learning for Predictive Maps in Python and Leaflet course will assist you in building relevant skills that will help you find a job in the related sectors. Also, the Certificate you’ll get after completing the Machine Learning for Predictive Maps in Python and Leaflet will put your head and shoulder above others in front of potential employers.

Become the person who would attract the results you seek. What you plant now, you will harvest later. So, grab this opportunity and start learning Machine Learning for Predictive Maps in Python and Leaflet!

QLS/ CPD/ CIQ Accredited
24/7 Assistance from our Support Team
100% Online
Self-paced course
Bite-sized Audio-visual Modules
Rich Learning Materials
Developed by Industry Specialists
Career Guidance

Learn at your own pace from the comfort of your home, as the rich learning materials of this premium course is accessible from any place at any time. The advanced course curriculums are divided into tiny bite-sized audio-visual modules by industry specialists with years of experience behind them.

Course Curriculum

Section 01: Introduction
	Introduction	00:10:00
Section 02: Setup and Installations
	Python Installation	00:04:00
	Creating a Python Virtual Environment	00:07:00
	Installing Django	00:09:00
	Installing Visual Studio Code IDE	00:06:00
	Installing PostgreSQL Database Server Part 1	00:03:00
	Installing PostgreSQL Database Server Part 2	00:09:00
Section 03: Writing the Django Server-Side Code
	Adding the settings.py Code	00:07:00
	Creating a Django Model	00:10:00
	Adding the admin.py Code	00:21:00
Section 04: Writing the Application Front-end Code
	Creating Template Files	00:10:00
	Creating Django Views	00:10:00
	Creating URL Patterns for the REST API	00:09:00
	Adding the index.html code	00:04:00
	Adding the layout.html code	00:19:00
	Creating our First Map	00:10:00
	Adding Markers	00:16:00
Section 05: Machine Learning
	Installing Jupyter Notebook	00:07:00
	Data Pre-processing	00:31:00
	Model Selection	00:20:00
	Model Evaluation and Building a Prediction Dataset	00:11:00
Section 06: Automating the Machine Learning Pipeline
	Creating a Django Model	00:04:00
	Embedding the Machine Learning Pipeline in the Application	00:42:00
	Creating a URL Endpoint for our Prediction Dataset	00:06:00
Section 07: Leaflet Programming
	Creating Multiple Basemaps	00:09:00
	Creating the Marker Layer Group	00:10:00
	Creating the Point Layer Group	00:12:00
	Creating the Predicted Point Layer Group	00:07:00
	Creating the Predicted High Risk Point Layer Group	00:12:00
	Creating the Legend	00:09:00
	Creating the Prediction Score Legend	00:15:00
Section 08: Project Source Code
	Resource	00:00:00