Отзывы учащихся о курсе Classify Radio Signals from Space using Keras от партнера Coursera Project Network

need more attention to theory behind and working of functions

No explanations from the basics of the imported libraries.

Excellent course, I really learned a lot by doing the programming part live, while watching the lectures. The sad part was Rhyme could provide me only a little time to use the cloud desktop. Creating a CNN model and seeing it work was amazing. I feel confident that I can apply the same to other data and also tweak some parameters so that it can be understood better.

Some more details can be inserted for more satellite images. Also there should be at least 2-3 different examples in the project for better understanding of the background fundamentals used behind this code.

The explanations were elaborate and insightful. But the choice of hyperparams seemed to be arbitrary and no justification was provided for it.

Great course. Instructor knows the subject well and guides you through the material explaining each part. Thank you

IT WAS GREAT EXPERIENCE TO WORK AND PERFORM THIS AMAZING PROJECT WITH SNEHAN KEKRE SIR

One of the best guided project ever.

It was really good project.

Thankyou Sir, Well taught.

very useful course

EXCELLENT

EXCELLENT

Thanks

good..

Good

Good

The course could be more effective if the teaching learning process was simple

good

good

nice

I have a basic knowledge in Deep Learning , so i was confident that i could learn this Project. It was little difficult but at the end i felt happy that I got try out & learn something interesting from this Project.

A very well-structured project. Surely, gave me a wonderful insight into building my own CNN.

However, the cloud platform was lagging and slow. Could have been a better user experience.

Using the Rhyme platform is unstable. Some of the functions are not available for the student. Correcting the way the Rhyme platform jumps around is frustrating.

Good for people who already know the basics of deep learning and can work with CNNs.