We may earn an affiliate commission when you visit our partners.
Course image
Course image
Coursera logo

Visual Machine Learning with Yellowbrick

Snehan Kekre

Welcome to this project-based course on Visual Machine Learning with Yellowbrick. In this course, we will explore how to evaluate the performance of a random forest classifier on the Poker Hand data set using visual diagnostic tools from Yellowbrick. With an emphasis on visual steering of our analysis, we will cover the following topics in our machine learning workflow: feature analysis, feature importance, algorithm selection, model evaluation using regression, cross-validation, and hyperparameter tuning.

Read more

Welcome to this project-based course on Visual Machine Learning with Yellowbrick. In this course, we will explore how to evaluate the performance of a random forest classifier on the Poker Hand data set using visual diagnostic tools from Yellowbrick. With an emphasis on visual steering of our analysis, we will cover the following topics in our machine learning workflow: feature analysis, feature importance, algorithm selection, model evaluation using regression, cross-validation, and hyperparameter tuning.

This course runs on Coursera's hands-on project platform called Rhyme. On Rhyme, you do projects in a hands-on manner in your browser. You will get instant access to pre-configured cloud desktops containing all of the software and data you need for the project. Everything is already set up directly in your internet browser so you can just focus on learning. For this project, you’ll get instant access to a cloud desktop with Python, Jupyter, Yellowbrick, and scikit-learn pre-installed.

Notes:

- You will be able to access the cloud desktop 5 times. However, you will be able to access instructions videos as many times as you want.

- This course works best for learners who are based in the North America region. We’re currently working on providing the same experience in other regions.

Enroll now

What's inside

Syllabus

Project: Visual Machine Learning with Yellowbrick
Welcome to this project-based course on Visual Machine Learning with Yellowbrick. In this course, we will explore how to evaluate the performance of a random forest classifier on the Poker Hand data set using visual diagnostic tools from Yellowbrick. With an emphasis on visual steering of our analysis, we will cover the following topics in our machine learning workflow: feature analysis, feature importance, algorithm selection, model evaluation using regression, cross-validation, and hyperparameter tuning.

Good to know

Know what's good
, what to watch for
, and possible dealbreakers
Suitable for beginners eager to enter the Machine Learning field
Leverages a cloud desktop interface for seamless hands-on learning
Focuses on visual machine learning techniques, which are valuable in industry
Covers comprehensive machine learning workflow steps, from data exploration to model evaluation
Emphasizes the practical application of machine learning concepts

Save this course

Save Visual Machine Learning with Yellowbrick to your list so you can find it easily later:
Save

Reviews summary

Helpful visual machine learning course

Learners say that Visual Machine Learning with Yellowbrick is a helpful course that provides practice quizzes. They greatly appreciate the guided projects included in the course.
Helpful practice quizzes included.
"This is a better-planned guided project with practice quizzes which really helps."
Course provides guided projects.
"This is a better-planned guided project.."
"really enjoyed this project."
"So I would definitely like to recommend this course for those who wants to have a knowledge on visual machine learning."

Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Visual Machine Learning with Yellowbrick with these activities:
Take the Yellobrick tutorial
Deepen your understanding of Python, Jupyter, and Yellowbrick before starting the course.
Browse courses on Yellowbrick
Show steps
  • Go to the Yellowbrick website.
  • Click on the "Tutorials" tab.
  • Choose a tutorial that interests you.
  • Follow the steps in the tutorial.
Review 'Machine Learning for Beginners' by Manning Publications
Strengthen your foundational understanding of machine learning concepts.
Show steps
  • Read through the book and highlight key concepts.
  • Summarize the main ideas of each chapter in your own words.
  • Discuss the book's content with peers or an instructor to enhance your understanding.
Follow the official Yellowbrick documentation
Stay up-to-date on the latest features and best practices for using Yellowbrick.
Browse courses on Yellowbrick
Show steps
  • Go to the Yellowbrick documentation website.
  • Read the tutorials.
  • Follow the code examples.
  • Try out the exercises.
11 other activities
Expand to see all activities and additional details
Show all 14 activities
Organize and review course materials
Improve your retention and understanding by organizing and reviewing course materials.
Show steps
  • Create a dedicated folder or notebook for course materials.
  • Organize materials by topic or module.
  • Review materials regularly to reinforce your learning.
Explore Yellowbrick documentation
Familiarize yourself with Yellowbrick's capabilities to enhance your learning.
Browse courses on Yellowbrick
Show steps
  • Visit the Yellowbrick website and read through the documentation.
  • Follow the tutorials provided by Yellowbrick to gain hands-on experience.
  • Experiment with different Yellowbrick visualization tools using the provided examples.
Join a Yellowbrick study group
Connect with other learners and collaborate on projects to enhance your understanding.
Browse courses on Yellowbrick
Show steps
  • Find a study group that meets your needs.
  • Attend the study group meetings.
  • Participate in discussions.
  • Work on projects with other members.
Practice feature analysis
Enhance your understanding of feature analysis by working through practice problems.
Browse courses on Feature Analysis
Show steps
  • Find online resources or textbooks that provide practice problems on feature analysis.
  • Set aside dedicated study time to work through the practice problems.
  • Review your answers and identify areas where you need improvement.
Practice using Yellowbrick's visualizers
Strengthen your skills in using Yellowbrick to analyze and visualize machine learning data.
Browse courses on Machine Learning Tools
Show steps
  • Load the Yellowbrick documentation.
  • Choose a visualizer that interests you.
  • Follow the instructions for using the visualizer.
  • Experiment with different settings.
Form peer study groups
Improve your understanding by discussing course concepts with peers.
Browse courses on Python
Show steps
  • Identify other students in the course who are interested in forming a study group.
  • Decide on a meeting schedule and location.
  • Prepare discussion topics for each meeting.
Mentor a junior developer or student who is learning Yellowbrick
Deepen your understanding of Yellowbrick and help others succeed.
Browse courses on Yellowbrick
Show steps
  • Find someone who is interested in learning Yellowbrick.
  • Set up a regular meeting time.
  • Share your knowledge and experience.
  • Answer their questions.
Write a blog post or article about your experience using Yellowbrick
Share your knowledge and insights about Yellowbrick with the broader community.
Browse courses on Data Visualization
Show steps
  • Choose a topic that you're knowledgeable about.
  • Write a draft of your post or article.
  • Get feedback from others.
  • Publish your post or article.
Create a visual representation of the Random Forest algorithm
Solidify your understanding of the Random Forest algorithm by creating a visual representation.
Browse courses on Random Forest
Show steps
  • Research different ways to visually represent the Random Forest algorithm.
  • Choose a representation method and gather the necessary data.
  • Create your visual representation using tools such as diagrams, flowcharts, or mind maps.
  • Present your visual representation to your peers or instructor for feedback.
Contribute to the Yellowbrick open-source project
Deepen your understanding of Yellowbrick by contributing to its development.
Browse courses on Yellowbrick
Show steps
  • Explore the Yellowbrick GitHub repository and identify areas where you can contribute.
  • Fork the repository and create a new branch for your changes.
  • Implement your changes and write unit tests to ensure functionality.
  • Submit a pull request to the main Yellowbrick repository.
Participate in a machine learning hackathon
Challenge yourself and apply your skills in a real-world machine learning scenario.
Browse courses on Machine Learning
Show steps
  • Find a machine learning hackathon that aligns with your interests and skill level.
  • Form a team or work independently on a project that addresses a specific problem statement.
  • Develop a machine learning solution and prepare a presentation for the hackathon.
  • Present your project to a panel of judges and receive feedback on your work.

Career center

Learners who complete Visual Machine Learning with Yellowbrick will develop knowledge and skills that may be useful to these careers:
Data Scientist
Data Scientists are responsible for collecting, cleaning, and analyzing data to help businesses make informed decisions. Visual Machine Learning with Yellowbrick is a great course for aspiring Data Scientists because it provides them with the skills to visually evaluate the performance of machine learning models. This course will help Data Scientists to make better decisions about which models to use and how to tune them for optimal performance.
Machine Learning Engineer
Machine Learning Engineers are responsible for building and deploying machine learning models. Visual Machine Learning with Yellowbrick is a great course for aspiring Machine Learning Engineers because it provides them with the skills to visually evaluate the performance of machine learning models. This course will help Machine Learning Engineers to build more accurate and reliable models.
Data Analyst
Data Analysts are responsible for collecting, cleaning, and analyzing data to help businesses make informed decisions. Visual Machine Learning with Yellowbrick is a great course for aspiring Data Analysts because it provides them with the skills to visually evaluate the performance of machine learning models. This course will help Data Analysts to make better decisions about which models to use and how to tune them for optimal performance.
Business Intelligence Analyst
Business Intelligence Analysts are responsible for collecting, cleaning, and analyzing data to help businesses make informed decisions. Visual Machine Learning with Yellowbrick is a great course for aspiring Business Intelligence Analysts because it provides them with the skills to visually evaluate the performance of machine learning models. This course will help Business Intelligence Analysts to make better decisions about which models to use and how to tune them for optimal performance.
Statistician
Statisticians are responsible for collecting, cleaning, and analyzing data to help businesses make informed decisions. Visual Machine Learning with Yellowbrick is a great course for aspiring Statisticians because it provides them with the skills to visually evaluate the performance of machine learning models. This course will help Statisticians to make better decisions about which models to use and how to tune them for optimal performance.
Software Engineer
Software Engineers are responsible for designing, developing, and maintaining software applications. Visual Machine Learning with Yellowbrick may be useful for aspiring Software Engineers because it provides them with the skills to visually evaluate the performance of machine learning models. This course may help Software Engineers to build more accurate and reliable software applications.
Product Manager
Product Managers are responsible for managing the development and launch of new products. Visual Machine Learning with Yellowbrick may be useful for aspiring Product Managers because it provides them with the skills to visually evaluate the performance of machine learning models. This course may help Product Managers to make better decisions about which products to develop and how to market them.
Marketing Manager
Marketing Managers are responsible for developing and executing marketing campaigns. Visual Machine Learning with Yellowbrick may be useful for aspiring Marketing Managers because it provides them with the skills to visually evaluate the performance of machine learning models. This course may help Marketing Managers to make better decisions about which marketing campaigns to run and how to target them.
Sales Manager
Sales Managers are responsible for leading and motivating sales teams. Visual Machine Learning with Yellowbrick may be useful for aspiring Sales Managers because it provides them with the skills to visually evaluate the performance of machine learning models. This course may help Sales Managers to make better decisions about which sales strategies to use and how to target them.
Financial Analyst
Financial Analysts are responsible for analyzing financial data and making recommendations. Visual Machine Learning with Yellowbrick may be useful for aspiring Financial Analysts because it provides them with the skills to visually evaluate the performance of machine learning models. This course may help Financial Analysts to make better decisions about which investments to make and how to manage risk.
Operations Manager
Operations Managers are responsible for planning and executing operations. Visual Machine Learning with Yellowbrick may be useful for aspiring Operations Managers because it provides them with the skills to visually evaluate the performance of machine learning models. This course may help Operations Managers to make better decisions about which processes to implement and how to improve efficiency.
Human Resources Manager
Human Resources Managers are responsible for managing the human resources of an organization. Visual Machine Learning with Yellowbrick may be useful for aspiring Human Resources Managers because it provides them with the skills to visually evaluate the performance of machine learning models. This course may help Human Resources Managers to make better decisions about which hiring and firing decisions to make and how to develop employees.
Customer Success Manager
Customer Success Managers are responsible for ensuring that customers are satisfied with their products and services. Visual Machine Learning with Yellowbrick may be useful for aspiring Customer Success Managers because it provides them with the skills to visually evaluate the performance of machine learning models. This course may help Customer Success Managers to make better decisions about which customer service strategies to use and how to target them.
Project Manager
Project Managers are responsible for planning and executing projects. Visual Machine Learning with Yellowbrick may be useful for aspiring Project Managers because it provides them with the skills to visually evaluate the performance of machine learning models. This course may help Project Managers to make better decisions about which projects to undertake and how to manage them.
Consultant
Consultants are responsible for providing advice and guidance to clients. Visual Machine Learning with Yellowbrick may be useful for aspiring Consultants because it provides them with the skills to visually evaluate the performance of machine learning models. This course may help Consultants to make better decisions about which advice to give and how to present it.

Reading list

We've selected 14 books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in Visual Machine Learning with Yellowbrick.
Provides a probabilistic approach to machine learning, covering topics such as Bayesian inference and graphical models.
Provides a gentle introduction to machine learning concepts and algorithms, focusing on Python implementation.
Provides a concise and accessible introduction to machine learning concepts and algorithms.
Provides a non-technical introduction to machine learning concepts and algorithms.

Share

Help others find this course page by sharing it with your friends and followers:

Similar courses

Here are nine courses similar to Visual Machine Learning with Yellowbrick.
Perform Feature Analysis with Yellowbrick
Most relevant
Analyze Text Data with Yellowbrick
Most relevant
Evaluate Machine Learning Models with Yellowbrick
Most relevant
Regression Analysis with Yellowbrick
Most relevant
Build an E-commerce Dashboard with Figma
Most relevant
Linear Regression with NumPy and Python
Most relevant
Computer Vision - Image Basics with OpenCV and Python
Most relevant
Data Visualization with Plotly Express
Most relevant
Deploy Models with TensorFlow Serving and Flask
Most relevant
Our mission

OpenCourser helps millions of learners each year. People visit us to learn workspace skills, ace their exams, and nurture their curiosity.

Our extensive catalog contains over 50,000 courses and twice as many books. Browse by search, by topic, or even by career interests. We'll match you to the right resources quickly.

Find this site helpful? Tell a friend about us.

Affiliate disclosure

We're supported by our community of learners. When you purchase or subscribe to courses and programs or purchase books, we may earn a commission from our partners.

Your purchases help us maintain our catalog and keep our servers humming without ads.

Thank you for supporting OpenCourser.

© 2016 - 2024 OpenCourser