jcg
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.
Specification: Convolutional Neural Networks for Medical Images Diagnosis
|
11 reviews for Convolutional Neural Networks for Medical Images Diagnosis
Show all
Most Helpful
Highest Rating
Lowest Rating
Add a review
| Price | $10.99 |
|---|---|
| Provider | |
| Duration | 1.5 hours |
| Year | 2020 |
| Level | Intermediate |
| Language | English |
| Certificate | Yes |
| Quizzes | No |
Convolutional Neural Networks for Medical Images Diagnosis
$10.99
Maath AlMulhim –
It is a brilliant course that combine analysis, programming, and statistics.
Qusay Shihab Hamad –
the course is so helpful and amazing, the lecturer was focused on the important topics without waste time. great work Dr.Hussien
Swati Zambre –
Very Informative Course
Rishibalaji –
Concise Explanation of important concepts using Keras
Alex0115 –
Very clear and detailed steps of the real world example for the CNN classifier
Worawit Saetan –
Well organized content and clear explanation, lots of invaluable information. Can’t wait to see the next course of this Medical Imaging series.
Yosuke K –
There is no instruction of coding actually to create the model of CNN. I wanted to see how to code and what the result shows up.
Leandrit F –
It was amazing how fast and clear he covers important topics. If you want to have the bigger picture of how a real world project is done, this course does a great justice to that.
Richard Yin –
very useful and helpful.
Bogdan Ioan Bustan –
The course is orientated towards the practical side and is fast paced. If you know the basics of Python, Keras and CNNs you get a quick rundown of the whole process from training and evaluation to deployment. All in all, this is a good course.
Deniz Katircioglu Ozturk –
More technical details must be supplied for backpropagation, optimizers, different models in transfer learning. Unfortunately, it all wrapped too quickly.