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Principal Component Analysis (PCA) in Python
This course introduces the fundamental concepts of dimensionality reduction and explores the technique of PCA in detail along with its Python implementation on a real-world business scenario.
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1 Video
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1 Coding Case
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1 Reading
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1 Quiz
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Difficulty: Beginner
No prior education or professional experience required
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Duration: Approximately 3 hours
Course Overview
- Many machine learning problems involve thousands or millions of features in the data. With these many features, not only is the processing is slow but finding the optimal solution is also challenging.
- This problem is handled using the dimensionality reduction algorithm. One such technique is Principal Component Analysis or PCA.
- Learn all the fundamental concepts behind the working of PCA technique and its implementation in Python.
- Gain practical experience by applying the knowledge and coding skills on real-world based business scenarios.
What’s included
Flexible Scheduling
Start learning online immediately, at your own pace
Desktop Only
We recommend completing this project on a desktop
Skills you will learn
Associated Learning Tracks
How it Works
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With our hands-on projects, you will take your newly learned skills along with our 750+ low-code/no-code functions and embedded coding console to complete milestone-based projects. Once completed, you will have effectively applied new skills and concepts to real-world data cases that can be translated directly into your career.
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Our courses include readings, videos, quizzes, and hands-on data cases that are completed using our virtual lab; give learners an applied learning experience.
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