Spatial Data Visualization and Machine Learning in Python

Spatial Data Visualization and Machine Learning in Python, available at $49.99, has an average rating of 4.1, with 21 lectures, based on 27 reviews, and has 130 subscribers.

You will learn about Data Visualization Data Analysis Data Transformation and Manipulation Python and Bokeh Geospatial Machine Learning Geo Mapping Python Programming Creating Dashboards This course is ideal for individuals who are Python Developers at any level or GIS Developers at any level or Developers at any level or Machine Learning engineers at any level or The curious mind It is particularly useful for Python Developers at any level or GIS Developers at any level or Developers at any level or Machine Learning engineers at any level or The curious mind.

Enroll now: Spatial Data Visualization and Machine Learning in Python

Summary

Title: Spatial Data Visualization and Machine Learning in Python

Price: $49.99

Average Rating: 4.1

Number of Lectures: 21

Number of Published Lectures: 21

Number of Curriculum Items: 21

Number of Published Curriculum Objects: 21

Original Price: R799.99

Quality Status: approved

Status: Live

What You Will Learn

Data Visualization

Data Analysis

Data Transformation and Manipulation

Python and Bokeh

Geospatial Machine Learning

Geo Mapping

Python Programming

Creating Dashboards

Who Should Attend

Python Developers at any level

GIS Developers at any level

Developers at any level

Machine Learning engineers at any level

The curious mind

Target Audiences

Python Developers at any level

GIS Developers at any level

Developers at any level

Machine Learning engineers at any level

The curious mind

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

Course Curriculum

Chapter 1: Introduction

Lecture 1: Introduction

Chapter 2: Setup and Installations

Lecture 1: Python Installation

Lecture 2: Installing Bokeh

Chapter 3: Data Preparation

Lecture 1: Data Preparation

Chapter 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

Chapter 5: Machine Learning

Lecture 1: Data Pre-processing

Lecture 2: Building a Predictive Model

Lecture 3: Building a Prediction Dataset

Chapter 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

Chapter 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

Chapter 8: Project Source Code

Lecture 1: Source Code and Notebook

Instructors

EBISYS R&D
Big Data Engineering

Rating Distribution

1 stars: 1 votes

2 stars: 2 votes

3 stars: 3 votes

4 stars: 14 votes

5 stars: 7 votes

Frequently Asked Questions

How long do I have access to the course materials?

You can view and review the lecture materials indefinitely, like an on-demand channel.

Can I take my courses with me wherever I go?

Definitely! If you have an internet connection, courses on Udemy are available on any device at any time. If you don’t have an internet connection, some instructors also let their students download course lectures. That’s up to the instructor though, so make sure you get on their good side!