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Unsupervised Learning: Dimensionality Reduction with Python
Dimensionality reduction involves transforming complex, high-dimensional data into a simpler, more manageable format, facilitating easier analysis. This course covers various Principal Component Analysis and Manifold Learning applications, utilizing Python for practical data analysis implementations.
6 minutes
Video Time
22 minutes
Ebooks Time
2 (no grades)
Quizzes
6
Notebooks
1 (15 questions)
Exam
1
Certificate
Gladys Casas-Cardoso
Data Scientist, Statistician, Instructor
About me
I am a Mathematics and Computer Sciences professor since 1994. With a master's degree in Mathematics and a Ph.D. in Technical Sciences, I enjoy teaching at all levels and ages.
I look forward to sharing my love of building meaningful and compelling content with all students to develop their data analysis abilities.
David Izada-Rodriguez
Computer Scientist, Software Engineer, Instructor
About me
After years of researching and teaching Computer Science, I switched to its applications to several industries. This experience allowed me to develop general-purpose techniques to be used from the factory floor to enterprise applications on the cloud. As I did at the beginning of my career, I am ready to share my experience.
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