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学生对 Coursera Project Network 提供的 Classify Radio Signals from Space using Keras 的评价和反馈

4.5
231 个评分
37 条评论

课程概述

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....

热门审阅

SB
May 23, 2020

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

IK
Oct 29, 2020

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

筛选依据:

1 - Classify Radio Signals from Space using Keras 的 25 个评论(共 37 个)

创建者 tejasva s

May 13, 2020

need more attention to theory behind and working of functions

创建者 Praveen K

Apr 29, 2020

No explanations from the basics of the imported libraries.

创建者 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.

创建者 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.

创建者 JAYDEEP D D

Jun 7, 2020

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

创建者 Prithviraj P G

May 4, 2020

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

创建者 Srivishnu. S

Jul 8, 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.

创建者 Isuru K

Oct 30, 2020

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

创建者 Adarsh M L

Jul 19, 2020

One of the best guided project ever.

创建者 Dipraj C J

Jun 12, 2020

It was really good project.

创建者 Mayank S

May 11, 2020

Thankyou Sir, Well taught.

创建者 Gangone R

Jul 2, 2020

very useful course

创建者 SASI V T

Jul 12, 2020

EXCELLENT

创建者 Anitha V

Jul 12, 2020

EXCELLENT

创建者 Santiago G

Sep 21, 2020

Thanks

创建者 GUNDABATTINA T

May 22, 2020

good..

创建者 aithagoni m

Aug 6, 2020

good

创建者 p s

Jun 23, 2020

Good

创建者 sarithanakkala

Jun 23, 2020

Good

创建者 tale p

Jun 22, 2020

good

创建者 Vajinepalli s s

Jun 16, 2020

nice

创建者 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.

创建者 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.

创建者 Thomas N

Sep 4, 2020

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.

创建者 Sagnik S

Jun 14, 2020

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