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

4.4
звезд
Оценки: 183
Рецензии: 33

О курсе

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....

Лучшие рецензии

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

Фильтр по:

1–25 из 33 отзывов о курсе Classify Radio Signals from Space using Keras

автор: tejasva s

May 13, 2020

need more attention to theory behind and working of functions

автор: Praveen K

Apr 29, 2020

No explanations from the basics of the imported libraries.

автор: 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.

автор: Prithviraj P G

May 04, 2020

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

автор: Srivishnu. S

Jul 08, 2020

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.

автор: 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.

автор: JAYDEEP D D

Jun 07, 2020

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

автор: Adarsh M L

Jul 19, 2020

One of the best guided project ever.

автор: Dipraj C J

Jun 12, 2020

It was really good project.

автор: Mayank S

May 11, 2020

Thankyou Sir, Well taught.

автор: Gangone R

Jul 02, 2020

very useful course

автор: SASI V T

Jul 13, 2020

EXCELLENT

автор: Anitha V

Jul 13, 2020

EXCELLENT

автор: GUNDABATTINA T

May 22, 2020

good..

автор: p s

Jun 24, 2020

Good

автор: sarithanakkala

Jun 23, 2020

Good

автор: tale p

Jun 22, 2020

good

автор: Vajinepalli s s

Jun 16, 2020

nice

автор: 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.

автор: 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.

автор: Sagnik S

Jun 14, 2020

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

автор: Jayesh K T

May 12, 2020

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

автор: Grace G N B

Jul 09, 2020

Thanks very much to COursera and special thanks to our mentor Snehan Kekre

автор: hari n s a u

Apr 28, 2020

good in handling the project ,step by step process

автор: ROHIT R N

Jun 05, 2020

Really a good Course