Machine Learning for Predictive Maps in Python and Leaflet

Description

This comprehensive course on Machine Learning for Predictive Maps in Python and Leaflet will deepen your understanding on this topic.

After successful completion of this course you can acquire the required skills in this sector. This Machine Learning for Predictive Maps in Python and Leaflet comes with accredited certification from CPD, which will enhance your CV and make you worthy in the job market.

So enrol in this course today to fast track your career ladder.

You may have to take a quiz or a written test online during or after the course. After successfully completing the course, you will be eligible for the certificate.

There is no experience or previous qualifications required for enrolment on this Machine Learning for Predictive Maps in Python and Leaflet. It is available to all students, of all academic backgrounds.

Our Machine Learning for Predictive Maps in Python and Leaflet is fully compatible with PC's, Mac's, Laptop, Tablet and Smartphone devices. This course has been designed to be fully compatible with tablets and smartphones so you can access your course on Wi-Fi, 3G or 4G.

There is no time limit for completing this course, it can be studied in your own time at your own pace.

Learning this new skill will help you to advance in your career. It will diversify your job options and help you develop new techniques to keep up with the fast-changing world. This skillset will help you to-

And much more!

9 sections • 33 lectures • 05:59:00 total length

•Introduction: 00:10:00

•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

•Adding the settings.py Code: 00:07:00

•Creating a Django Model: 00:10:00

•Adding the admin.py Code: 00:21:00

•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

•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

•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

•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

•Resource: 00:00:00

•Assignment - Machine Learning for Predictive Maps in Python and Leaflet: 00:00:00