Name: Visualizing Filters of a CNN using TensorFlow
Brand: Coursera
Availability: OnlineOnly
Rating: 4.4 (10 reviews)

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课程概述

In this short, 1 hour long guided project, we will use a Convolutional Neural Network - the popular VGG16 model, and we will visualize various filters from different layers of the CNN. We will do this by using gradient ascent to visualize images that maximally activate specific filters from different layers of the model. We will be using TensorFlow as our machine learning framework. The project uses the Google Colab environment which is a fantastic tool for creating and running Jupyter Notebooks in the cloud, and Colab even provides free GPUs for your notebooks. You will need prior programming experience in Python. This is a practical, hands on guided project for learners who already have theoretical understanding of Neural Networks, Convolutional Neural Networks, and optimization algorithms like gradient descent but want to understand how to use the TensorFlow to visualize various filters of a CNN. 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....

1 - Visualizing Filters of a CNN using TensorFlow 的 10 个评论（共 10 个）

创建者 Azadeh S

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Jan 14, 2025

I would like to know how to make filters for different projects. for example how to make filters for extract corners, etc.

创建者 JAMIL A

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Oct 24, 2023

Love the way he explain the code in simple and cool manner

创建者 Kenneth N

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Jul 4, 2022

very well prepared and explained. but colab is slow

创建者 Shadi Q

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Jan 18, 2023

Clear and easy explanation

创建者 Libero P

•

Sep 7, 2025

Πολύ καλό μάθημα

创建者 Pooja.Bidwai p

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Dec 13, 2021

awesome

创建者 Fabian B

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Apr 14, 2022

instructor explains everything clearly, but an actual application was missing. a quick cats and dogs comparison on how to infer filter activation would have been helpful.