Course Curriculum
- 9 sections
- 33 lectures
- 5 hours, 59 minutes total length
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Introduction00:10:00
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Python Installation00:04:00
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Creating a Python Virtual Environment00:07:00
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Installing Django00:09:00
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Installing Visual Studio Code IDE00:06:00
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Installing PostgreSQL Database Server Part 100:03:00
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Installing PostgreSQL Database Server Part 200:09:00
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Adding the settings.py Code00:07:00
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Creating a Django Model00:10:00
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Adding the admin.py Code00:21:00
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Creating Template Files00:10:00
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Creating Django Views00:10:00
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Creating URL Patterns for the REST API00:09:00
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Adding the index.html code00:04:00
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Adding the layout.html code00:19:00
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Creating our First Map00:10:00
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Adding Markers00:16:00
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Installing Jupyter Notebook00:07:00
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Data Pre-processing00:31:00
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Model Selection00:20:00
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Model Evaluation and Building a Prediction Dataset00:11:00
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Creating a Django Model00:04:00
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Embedding the Machine Learning Pipeline in the Application00:42:00
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Creating a URL Endpoint for our Prediction Dataset00:06:00
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Creating Multiple Basemaps00:09:00
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Creating the Marker Layer Group00:10:00
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Creating the Point Layer Group00:12:00
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Creating the Predicted Point Layer Group00:07:00
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Creating the Predicted High Risk Point Layer Group00:12:00
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Creating the Legend00:09:00
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Creating the Prediction Score Legend00:15:00
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Resource
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Assignment – Machine Learning for Predictive Maps in Python and Leaflet