- Course Highlights
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.
Course Curriculum
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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1 Year Access 
8 Students -
5 hours, 59 minutes