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
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(293 reviews)
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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
Skills you'll practice
Details to know
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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.
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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.
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Reviewed on Aug 4, 2020
It's a good course for someone to try out his knowledge of the basic packages and the concepts and the maths behind PCA.
Reviewed on Apr 24, 2020
Learned Applying PCA
Reviewed on Oct 30, 2020
Good Introductory project to gain insights into PCA using Numpy and python.
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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.