Machine Learning for Predictive Maps in Python and Leaflet
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Machine Learning for Predictive Maps in Python and Leaflet teaches how to build intelligent geospatial models, analyse data patterns, and create interactive maps for real world decision making applications today.
Machine Learning for Predictive Maps in Python and Leaflet
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5 hours, 59 minutes
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Overview
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.
Course design
The course is delivered through our online learning platform, accessible through any internet-connected device. There are no formal deadlines or teaching schedules, meaning you are free to study the course at your own pace.
You are taught through a combination of
- Video lessons
- Online study materials
Will I receive a certificate of completion?
Upon successful completion, you will qualify for the UK and internationally-recognised CPD accredited certification. You can choose to make your achievement formal by obtaining your PDF Certificate at the cost of £9 and Hard Copy Certificate for £15.
Why study this course
It doesn’t matter if you are an aspiring professional or absolute beginner; this course will enhance your expertise and boost your CV with critical skills and an accredited certification attesting to your knowledge.
The Machine Learning for Predictive Maps in Python and Leaflet is fully available to anyone, and no previous qualifications are needed to enrol. All One Education needs to know is that you are eager to learn and are over 16.
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 | ||
| Assignment | |||
| Assignment – Machine Learning for Predictive Maps in Python and Leaflet | 00:00:00 | ||
