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This plan includes
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This plan includes
- Access to 11,000+ Courses
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HD Video Recorded Lectures- Learn on Mobile/PC/Tablet
- Quizzes and Real Projects
- Lifetime Course Certificate
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- Email & Chat Support
- Cancel Anytime
What you'll learn?
- Data Visualization
- Data Analysis
- Data Transformation and Manipulation
- Python and Bokeh
- Geospatial Machine Learning
- Geo Mapping
- Python Programming
- Creating Dashboards
Course Overview
Welcome to the 'Spatial Data Visualization and Machine Learning in Python' course. In this course we will be building a spatial data analytics dashboard using bokeh and python. Bokeh is a very powerful data visualization library that is used for building a wide range of interactive plots and dashboards using the python programming language. It also converts python code into html and JavaScript code, which allows plots to be hosted on servers and displayed in web browsers. We be building a predictive model that we will use to do a further analysis, on our data and plot it's forecast results alongside the dataset that we will be focusing on. We will be visualizing our data in a variety of bokeh charts, which we will explore in depth. Once we understand each plot in depth, we will be equipped with the knowledge to build a dashboard that we will use to analyze our data. And once we have built our dashboard, we will then create a lightweight server that we will use to serve our dashboard and make it accessible via a URL. You will learn how to visualize spatial data in maps and charts You will learn data analysis using jupyter notebook You will learn how to manipulate, clean and transform data You will learn how to use the Bokeh library You will learn machine learning with geospatial data You will learn basic geo mapping You will learn how to create dashboards
Pre-requisites
- Basic Understanding of Python
- Little or no understanding of GIS
- Basic understanding of Programming concepts
- Basic understanding of Data
- Basic understanding of what Machine Learning is
Target Audience
- Python Developers at any level
- GIS Developers at any level
- Developers at any level
- Machine Learning engineers at any level
- The curious mind
Curriculum 21 Lectures 00:04:21
-
Section 1 : Introduction
-
Section 2 : Setup and Installation
- Lecture 1 :
- Python Installation
- Lecture 2 :
- Installing Bokeh
-
Section 3 : Data Preparation
- Lecture 1 :
- Data Preparation
-
Section 4 : Data Visualization
- Lecture 1 :
- Creating a Bar Chart
- Lecture 2 :
- Creating a Line Chart
- Lecture 3 :
- Creating a Doughnut Chart
- Lecture 4 :
- Creating a Magnitude Plot
- Lecture 5 :
- Creating a Geo Map Plot
- Lecture 6 :
- Creating a Grid Plot
-
Section 5 : Machine Learning
- Lecture 1 :
- Data Pre-processing
- Lecture 2 :
- Building a Predictive Model
- Lecture 3 :
- Building a Prediction Dataset
-
Section 6 : Building the Dashboard
- Lecture 1 :
- Adding predicted data to our plots - Part 1
- Lecture 2 :
- Adding predicted data to our plots - Part 2
- Lecture 3 :
- Adding predicted data to our plots - Part 3
- Lecture 4 :
- Adding the Grid Plot
-
Section 7 : Creating the Dashboard Server
- Lecture 1 :
- Installing Visual Studio Code
- Lecture 2 :
- Creating the Project and Virtual Environment
- Lecture 3 :
- Building and Running the Server
-
Section 8 : Project Source Code
- Lecture 1 :
- Source Code and Notebook
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