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Facial Expression Recognition with Keras に戻る

Coursera Project Network による Facial Expression Recognition with Keras の受講者のレビューおよびフィードバック

4.5
800件の評価
121件のレビュー

コースについて

In this 2-hour long project-based course, you will build and train a convolutional neural network (CNN) in Keras from scratch to recognize facial expressions. The data consists of 48x48 pixel grayscale images of faces. The objective is to classify each face based on the emotion shown in the facial expression into one of seven categories (0=Angry, 1=Disgust, 2=Fear, 3=Happy, 4=Sad, 5=Surprise, 6=Neutral). You will use OpenCV to automatically detect faces in images and draw bounding boxes around them. Once you have trained, saved, and exported the CNN, you will directly serve the trained model to a web interface and perform real-time facial expression recognition on video and image data. 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 Keras 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

RD

Jul 04, 2020

All the concepts are well explained. The project gives a nice insight about how we can integrate different ML frameworks to build a project and also how to deploy the model as a web app by Flask.

GP

Jun 12, 2020

Very easy to follow and the instructor was very informative throughout the project. As a beginner myself, it was easy for me to follow along and understand the project

フィルター:

Facial Expression Recognition with Keras: 1 - 25 / 120 レビュー

by Tee R

Aug 22, 2020

A very nice project, although you need some understanding of the topic at hand before starting. Even though I did not know about deep learning before this project, I watched 3 Blue 1 Brown's first 2 videos about neural network, referred to some medium posts at Towards Data Science and read the Keras documentation when I did not understand something, and I found the project manageable.

by Ashok T

Jun 03, 2020

It was fun to read and learn form this course. I am very happy with the infra that was provided in this course - it was very smooth experience.

Also, kudos to the instructor for having a very precise even pace all throughout and teaching a very useful thing, and i hope i will build further on it.

by RUDRA P D

Jul 04, 2020

All the concepts are well explained. The project gives a nice insight about how we can integrate different ML frameworks to build a project and also how to deploy the model as a web app by Flask.

by Gayathri P

Jun 12, 2020

Very easy to follow and the instructor was very informative throughout the project. As a beginner myself, it was easy for me to follow along and understand the project

by Shivam R D

Jun 29, 2020

This project gave me complete knowledge for implementiing the face recognition in future.This help me to built an app using FLASK.Its a good project to start with.

by Jordan G

Jul 17, 2020

Great ressource to start practicing emotion recognition with famous domain's dataset FER. I also appreciate the using of web interface to display results.

by AVINASH K Y

Jun 01, 2020

Amazing start with having such types of the project by Coursera.

There is a lot to learn

This method of Teaching + Practical work simultaneously-----Amazing

by TUSHAR S

Sep 04, 2020

Nice project! but the code in camera.py and the main.py file which is used to create a flask app to serve predictions should be explained in more detail.

by Jiwan

Jul 31, 2020

Good project to know the pipeline and simple deployment. however basic understanding of the machine learning terminology is needed.

by Sumit K

May 30, 2020

Amazing Course as it provides learners, a facility of infrastructure as well as practise.

Great Experience, i learned a lot. !!!

by Tarek A Z

Jun 16, 2020

Very Good for a person who is starting Machine Learning/Deep Learning. Seeing your project into action gives you motivation.

by Priyanka N

Jun 09, 2020

The course was so amazing.

I learned alot from this course and all things are really well-explained by our instructor.

by Faizan A B

May 23, 2020

Learned a lot of new things. Instructor also explained deeply every thing. Overall, a comprehensive course of FER.

by Koustubh P

Jul 09, 2020

A really good practical course if you'd like to learn how to implement a live Facial Recognition System.

by SHIBU M

Aug 09, 2020

I really learned a lot from this project. I would like to join in more project-based courses like this.

by Adarsh S

May 21, 2020

A really good course on how to apply theoretical knowledge into real world.

Course instructor was great!

by Ling Z P

Jun 26, 2020

It was a useful and practical demonstration of CNN application on human expressions. Kudos.

by Shreya S

Jun 09, 2020

Thank you for providing such a wonderful course.Enjoyed working on this project thoroughly.

by Aastha A

Jun 09, 2020

This project is good but I don't understand about to download the material what I have done

by IT16151420 M A R L S

Jun 17, 2020

Best course for learning how to human emotions recognize using keras. Thank you very much.

by Salman A F

Jul 08, 2020

The course was straightforward into the main idea, but seems that the VM is a bit slow

by Akib J I

Jun 02, 2020

perfect course for beginners. step by step explanation makes it easier for learners.

by Sandeepa D K

Jul 22, 2020

perfect tutor for this kind of interactive course. Thank you for having this.

by Bhavya V

Sep 17, 2020

It was a good course. I was looking for something like this from a long time

by Dr.Kranti Z

Jun 02, 2020

A very good course on how to put on theoretical knowledge into actual world.