Course Information
Registration period
Year-round Recruitment
Course Level
Study Mode
Duration
1 Hour(s) 29 Minute(s)
Language
English
Taught by
Hussein Samma
Rating
Course Overview
CNN, Deep Learning, Medical Imaging, Transfer Learning, CNN Visualization, VGG, ResNet, Inception, Python & Keras
This course was designed and prepared to be a practical CNN-based medical diagnosis application. It focuses on understanding by examples how CNN layers are working, how to train and evaluate CNN, how to improve CNN performances, how to visualize CNN layers, and how to deploy the final trained CNN model.
All the development tools and materials required for this course are FREE. Besides that, all implemented Python codes are attached with this course.
Course Content
- 9 section(s)
- 29 lecture(s)
- Section 1 Introduction
- Section 2 Getting and Preparing Data
- Section 3 CNN Architecture
- Section 4 CNN Training
- Section 5 CNN Evaluation
- Section 6 CNN Improvement
- Section 7 CNN Transfer Learning
- Section 8 CNN Visualization
- Section 9 CNN Deployment
What You’ll Learn
- To build from scratch a CNN-based medical diagnosis model.
- To learn how to get and prepare medical dataset used in this work.
- To understand by examples how CNN layers are working.
- To learn by examples different measures which used to evaluate CNN.
- To learn different techniques used to improve the performances of CNN.
- To learn how to visualize CNN intermediate layers.
- To learn how to deploy the trained CNN model using flask API server.
- To learn how to implement all steps using python, tensorflow, and keras.
Skills covered in this course
Reviews
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SSiti Salasiah
The contents are good only the slang of the English is not quite clear. However, we can use the captions to get the wordings.
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BBrian Connololy
The instructor rarely explained why he was doing what he was doing, or why one NN architecture failed and the other succeeded. He would walk though the code in a couple of minutes, and present the result - good or bad. Also, there were bugs in the code, not entirely due to the packages being outdated.
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MMangal Sonone
Good explaination
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DDan Cacovean
The instructor explains the CNN pretty welll
