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Classify Radio Signals from Space using Keras に戻る

Coursera Project Network による Classify Radio Signals from Space using Keras の受講者のレビューおよびフィードバック

4.4
139件の評価
26件のレビュー

コースについて

In this 1-hour long project-based course, you will learn the basics of using Keras with TensorFlow as its backend and use it to solve an image classification problem. The data we are going to use consists of 2D spectrograms of deep space radio signals collected by the Allen Telescope Array at the SETI Institute. We will treat the spectrograms as images to train an image classification model to classify the signals into one of four classes. By the end of the project, you will have built and trained a convolutional neural network from scratch using Keras to classify signals from space. This course runs on Coursera's hands-on project platform called Rhyme. On Rhyme, you do projects in a hands-on manner in your browser. You will get instant access to pre-configured cloud desktops containing all of the software and data you need for the project. Everything is already set up directly in your internet browser so you can just focus on learning. For this project, you’ll get instant access to a cloud desktop with Python, Jupyter, and Tensorflow pre-installed. Notes: - You will be able to access the cloud desktop 5 times. However, you will be able to access instructions videos as many times as you want. - 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....

人気のレビュー

SB

May 24, 2020

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

JD

Jun 07, 2020

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

フィルター:

Classify Radio Signals from Space using Keras: 1 - 25 / 26 レビュー

by tejasva s

May 13, 2020

need more attention to theory behind and working of functions

by Praveen K

Apr 29, 2020

No explanations from the basics of the imported libraries.

by Dr.Ravi K

Apr 25, 2020

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.

by Prithviraj P G

May 04, 2020

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

by Sudharsan B

May 24, 2020

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

by JAYDEEP D D

Jun 07, 2020

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

by Dipraj C J

Jun 12, 2020

It was really good project.

by Mayank S

May 11, 2020

Thankyou Sir, Well taught.

by Gangone R

Jul 02, 2020

very useful course

by GUNDABATTINA T

May 22, 2020

good..

by p s

Jun 24, 2020

Good

by sarithanakkala

Jun 23, 2020

Good

by tale p

Jun 22, 2020

good

by Vajinepalli s s

Jun 16, 2020

nice

by SanjaySuman S G

Jun 13, 2020

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.

by Ritesh C

Jun 10, 2020

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.

by Sagnik S

Jun 14, 2020

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

by Jayesh K T

May 12, 2020

Very nice and cool project. But, more explanation on the project is required.

by hari n s a u

Apr 28, 2020

good in handling the project ,step by step process

by ROHIT R N

Jun 05, 2020

Really a good Course

by Syed Z R Z

May 30, 2020

Could be better

by Iman R

Jun 04, 2020

I didn't know how other guided project works, but I think it's to short and lack of theory to make us understand. It's just straight away to implement some code. I think it could add a section that give us a reading or other material that can strength our knowledge on the project

by FARHANA S J

Jun 27, 2020

Overall good. But have a lot of bugs in the course design. Also needs a lot more theory explanation.

by Jayakrishnan K

Jun 14, 2020

It will be good if it provides more explanation about the matter in the video, Otherwise nice

by Stepan S

Jun 02, 2020

Rhyme experience is awful. "Connecting..." screen 80% of the time. 1h of videos and 1h for the lab is not enough.