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!
You may also like
- Top 10 Language Learning Courses to Learn in November 2024
- Top 10 Video Editing Courses to Learn in November 2024
- Top 10 Music Production Courses to Learn in November 2024
- Top 10 Animation Courses to Learn in November 2024
- Top 10 Digital Illustration Courses to Learn in November 2024
- Top 10 Renewable Energy Courses to Learn in November 2024
- Top 10 Sustainable Living Courses to Learn in November 2024
- Top 10 Ethical AI Courses to Learn in November 2024
- Top 10 Cybersecurity Fundamentals Courses to Learn in November 2024
- Top 10 Smart Home Technology Courses to Learn in November 2024
- Top 10 Holistic Health Courses to Learn in November 2024
- Top 10 Nutrition And Diet Planning Courses to Learn in November 2024
- Top 10 Yoga Instruction Courses to Learn in November 2024
- Top 10 Stress Management Courses to Learn in November 2024
- Top 10 Mindfulness Meditation Courses to Learn in November 2024
- Top 10 Life Coaching Courses to Learn in November 2024
- Top 10 Career Development Courses to Learn in November 2024
- Top 10 Relationship Building Courses to Learn in November 2024
- Top 10 Parenting Skills Courses to Learn in November 2024
- Top 10 Home Improvement Courses to Learn in November 2024