Welcome to this 2 hour long project-based course on Principal Component Analysis with NumPy and Python. In this project, you will do all the machine learning without using any of the popular machine learning libraries such as scikit-learn and statsmodels. The aim of this project and is to implement all the machinery of the various learning algorithms yourself, so you have a deeper understanding of the fundamentals. By the time you complete this project, you will be able to implement and apply PCA from scratch using NumPy in Python, conduct basic exploratory data analysis, and create simple data visualizations with Seaborn and Matplotlib. The prerequisites for this project are prior programming experience in Python and a basic understanding of machine learning theory.
Principal Component Analysis with NumPy
Instructor: Snehan Kekre
10,813 already enrolled
Included with 
(295 reviews)
Recommended experience
What you'll learn
Implement Principal Component Analysis (PCA) from scratch with NumPy and Python
Conduct basic exploratory data analysis (EDA)
Create simple data visualizations with Seaborn and Matplotlib
Details to know
Add to your LinkedIn profile
Only available on desktop
See how employees at top companies are mastering in-demand skills
Learn, practice, and apply job-ready skills in less than 2 hours
- Receive training from industry experts
- Gain hands-on experience solving real-world job tasks
- Build confidence using the latest tools and technologies
About this Guided Project
Learn step-by-step
In a video that plays in a split-screen with your work area, your instructor will walk you through these steps:
Introduction and Overview
Load the Data and Libraries
Visualize the Data
Data Standardization
Compute the Eigenvectors and Eigenvalues
Singular Value Decomposition (SVD)
Selecting Principal Components Using the Explained Variance
Project Data Onto a Lower-Dimensional Linear Subspace
Recommended experience
Prior programming experience in Python and machine learning theory is recommended.
4 project images
Instructor
Offered by
How you'll learn
Skill-based, hands-on learning
Practice new skills by completing job-related tasks.
Expert guidance
Follow along with pre-recorded videos from experts using a unique side-by-side interface.
No downloads or installation required
Access the tools and resources you need in a pre-configured cloud workspace.
Available only on desktop
This Guided Project is designed for laptops or desktop computers with a reliable Internet connection, not mobile devices.
Why people choose Coursera for their career
Learner reviews
295 reviews
- 5 stars
71.52%
- 4 stars
22.37%
- 3 stars
3.72%
- 2 stars
0.67%
- 1 star
1.69%
Showing 3 of 295
Reviewed on May 31, 2020
Course is amazing, got many concepts clear, learned a lot. Would also be great if more than one datasets are taken as excercise.
Reviewed on Apr 24, 2020
Learned Applying PCAConcise course.Liked the method of teaching.
Reviewed on Jul 25, 2020
Good Exercise to practice and understand a little better.
You might also like
Coursera Project Network
Imperial College London
Duke University
Coursera Project Network
New to Machine Learning? Start here.
Open new doors with Coursera Plus
Unlimited access to 10,000+ world-class courses, hands-on projects, and job-ready certificate programs - all included in your subscription
Advance your career with an online degree
Earn a degree from world-class universities - 100% online
Join over 3,400 global companies that choose Coursera for Business
Upskill your employees to excel in the digital economy
Frequently asked questions
By purchasing a Guided Project, you'll get everything you need to complete the Guided Project including access to a cloud desktop workspace through your web browser that contains the files and software you need to get started, plus step-by-step video instruction from a subject matter expert.
Because your workspace contains a cloud desktop that is sized for a laptop or desktop computer, Guided Projects are not available on your mobile device.
Guided Project instructors are subject matter experts who have experience in the skill, tool or domain of their project and are passionate about sharing their knowledge to impact millions of learners around the world.