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学生对 Coursera Project Network 提供的 Dimensionality Reduction using an Autoencoder in Python 的评价和反馈

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课程概述

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....

热门审阅

UI

May 3, 2020

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

RR

Jun 12, 2020

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

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1 - Dimensionality Reduction using an Autoencoder in Python 的 16 个评论(共 16 个)

创建者 Abhishek P G

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