Chevron Left
Zurück zu Dimensionality Reduction using an Autoencoder in Python

Bewertung und Feedback des Lernenden für Dimensionality Reduction using an Autoencoder in Python von Coursera Project Network

4.6
Sterne
94 Bewertungen

Über den Kurs

In this 1-hour long project, you will learn how to generate your own high-dimensional dummy dataset. You will then learn how to preprocess it effectively before training a baseline PCA model. You will learn the theory behind the autoencoder, and how to train one in scikit-learn. You will also learn how to extract the encoder portion of it to reduce dimensionality of your input data. In the course of this project, you will also be exposed to some basic clustering strength metrics. Note: 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....

Top-Bewertungen

UI

3. Mai 2020

Very practical and useful introductory course. Looking for the next courses :)

RR

12. Juni 2020

I really enjoyed this course. Thank you very much for the valuable teaching.

Filtern nach:

1 - 16 von 16 Bewertungen für Dimensionality Reduction using an Autoencoder in Python

von Abhishek P G

15. Juni 2020

von Felix H

30. Juni 2020

von Ulvi I

4. Mai 2020

von Ramya G R

13. Juni 2020

von Mayank S

4. Mai 2020

von Oscar A C B

12. Juni 2020

von chandrasekhar u

6. Mai 2020

von Gangone R

2. Juli 2020

von Doss D

2. Juli 2020

von Sarangan R

10. Jan. 2021

von Joerg A

19. Mai 2020

von M H

17. Sep. 2020

von Juan C V

5. Juli 2020

von Sujeet B

7. Mai 2020

von Jorge G

25. Feb. 2021

von Simon S R

29. Aug. 2020