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Machine Learning for Predictive Maps in Python and Leaflet
By Skill Up
(9)- 30 Day Money Back Guarantee
- Completion Certificate
- 24/7 Technical Support
Highlights
On-Demand course
5 hours 59 minutes
All levels
Description
Gain the skills and credentials to kickstart a successful career and learn from the experts with this step-by-step training course. This Machine Learning for Predictive Maps in Python and Leaflet has been specially designed to help learners gain a good command of Machine Learning for Predictive Maps in Python and Leaflet, providing them with a solid foundation of knowledge to become a qualified professional.
Through this Machine Learning for Predictive Maps in Python and Leaflet, you will gain both practical and theoretical understanding of Machine Learning for Predictive Maps in Python and Leaflet that will increase your employability in this field, help you stand out from the competition and boost your earning potential in no time.
Not only that, but this training includes up-to-date knowledge and techniques that will ensure you have the most in-demand skills to rise to the top of the industry. This qualification is fully accredited, broken down into several manageable modules, ideal for aspiring professionals.
Learning outcome
Get a deep understanding of the Machine Learning for Predictive Maps in Python and Leaflet just in hours not years
Familiar yourself with the recent development and updates of the relevant industry
Know how to use your theoretical and practical knowledge to adapt in any working environment
Get help from our expert tutors anytime you need
Access to course contents that are designed and prepared by industry professionals
Study at your convenient time and from wherever you want
Requirements
No formal qualifications required, anyone from any academic background can take this course.
Access to any internet-enabled smart device.
Why should I take this course?
Affordable premium-quality E-learning content, you can learn at your own pace.
You will receive a completion certificate upon completing the course.
Internationally recognized Accredited Qualification will boost up your resume.
You will learn the researched and proven approach adopted by successful people to transform their careers.
You will be able to incorporate various practical techniques successfully and understand your customers better.
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 - Machine Learning for Predictive Maps in Python and Leaflet | 🕐 00:00:00 | ||
Assignment | |||
Assignment - Machine Learning for Predictive Maps in Python and Leaflet | 🕐 00:00:00 |
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