Spatial Data Visualization and Machine Learning in Python

Building an Analytics Dashboard to Analyze and Predict Quakes using Bokeh and Python

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Last Updated: 2022-11-25 08:11:42 English Course Type: Self Learning

Data Visualization
Data Analysis
Data Transformation and Manipulation
Python and Bokeh
Geospatial Machine Learning
Geo Mapping
Python Programming
Creating Dashboards

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

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

Python Developers at any level
GIS Developers at any level
Developers at any level
Machine Learning engineers at any level
The curious mind

Section 1 : Introduction 1 Lectures 00:00:00
Lecture 1 :
Introduction Preview
Section 2 : Setup and Installation 2 Lectures 00:03:16
Lecture 1 :
Python Installation
Lecture 2 :
Installing Bokeh
Section 3 : Data Preparation 1 Lectures 00:00:00
Lecture 1 :
Data Preparation
Section 4 : Data Visualization 6 Lectures 00:00:02
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 3 Lectures 00:00:01
Lecture 1 :
Data Pre-processing
Lecture 2 :
Building a Predictive Model
Lecture 3 :
Building a Prediction Dataset
Section 6 : Building the Dashboard 4 Lectures 00:00:00
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 3 Lectures 00:01:02
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 1 Lectures
Lecture 1 :
Source Code and Notebook

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