https://github.com/camara94/visualizing-filters-cnn-tensorflow
Welcome to Visualizing Filters of a CNN using TensorFlow. This is a project-based course which should take less than 1 hours to finish. Before diving into the project, please take a look at the course objectives and structure:
https://github.com/camara94/visualizing-filters-cnn-tensorflow
cnn cnn-keras deep-learning gradient-descent logic-programming machine-learning tensorflow
Last synced: 2 months ago
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Welcome to Visualizing Filters of a CNN using TensorFlow. This is a project-based course which should take less than 1 hours to finish. Before diving into the project, please take a look at the course objectives and structure:
- Host: GitHub
- URL: https://github.com/camara94/visualizing-filters-cnn-tensorflow
- Owner: camara94
- Created: 2022-04-22T11:12:57.000Z (about 4 years ago)
- Default Branch: main
- Last Pushed: 2022-04-23T06:38:00.000Z (about 4 years ago)
- Last Synced: 2025-04-09T14:45:36.509Z (about 1 year ago)
- Topics: cnn, cnn-keras, deep-learning, gradient-descent, logic-programming, machine-learning, tensorflow
- Language: Jupyter Notebook
- Homepage:
- Size: 2.53 MB
- Stars: 2
- Watchers: 2
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# Visualizing Filters CNN Tensorflow
Welcome to Visualizing Filters of a CNN using TensorFlow. This is a project-based course which should take less than 1 hours to finish. Before diving into the project, please take a look at the course objectives and structure:
## Course Objectives
In this course, our primary learning objective is to visualize image features that maximally activate filters of a **CNN**.
## Course Structure
This course is divided into 3 parts:
1. Course Overview: This introductory reading material.
2. **Visualizing Filters of a CNN using TensorFlow**: This is the hands on project that we will work on in Rhyme.
3. Graded Quiz: This is the final assignment that you need to pass in order to finish the course successfully.
## Project Structure
The hands on project on **Visualizing Filters of a CNN using TensorFlow** is divided into following tasks:
**Task 1: Introduction**
**Task 2: Downloading the Model**
**Task 3: Get Submodels**
**Task 4: Image Visualization**
**Task 5: Training Loop**
**Task 6: Final Results**
## Link
[https://tfhub.dev/google/imagenet/efficientnet_v2_imagenet1k_b3/feature_vector/2](https://tfhub.dev/google/imagenet/efficientnet_v2_imagenet1k_b3/feature_vector/2)