Chevron Left
Вернуться к Facial Expression Recognition with Keras

Отзывы учащихся о курсе Facial Expression Recognition with Keras от партнера Coursera Project Network

4.5
звезд
Оценки: 919
Рецензии: 136

О курсе

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....

Лучшие рецензии

RD
3 июля 2020 г.

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.

IK
26 окт. 2020 г.

This is a great hands-on project ! It is very well designed, and the instructor guides you to do it step by step. I enjoy this learning and practicing process a lot. Thank you !

Фильтр по:

1–25 из 134 отзывов о курсе Facial Expression Recognition with Keras

автор: Tee R

22 авг. 2020 г.

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.

автор: Ashok T

3 июня 2020 г.

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.

автор: Omar M A

9 мая 2020 г.

Thanks for the content, I browsed this course to know how the instructor would deal with class imbalance problem, but he didn't handle it, and dealt with the problem as if the classes were balanced.

Also I noticed when he made the validation generator, he enabled shuffling which I think is wrong as you don't want to shuffle the validation set and each epoch have a different subset of validation set to evaluate your model, you need to make to make sure that the validation set doesn't change per epoch to serve its purpose of had the model improved during this epoch?

автор: RUDRA P D

4 июля 2020 г.

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.

автор: Feng J

7 окт. 2020 г.

This is a great hands-on project ! It is very well designed, and the instructor guides you to do it step by step. I enjoy this learning and practicing process a lot. Thank you !

автор: Gayathri P

12 июня 2020 г.

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

автор: Shivam R D

28 июня 2020 г.

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.

автор: Jordan G

17 июля 2020 г.

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

автор: AVINASH K Y

1 июня 2020 г.

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

автор: TUSHAR S

4 сент. 2020 г.

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.

автор: Murtuza B

21 сент. 2020 г.

The explanation provided by the mentor is really good! I like the way the project was compiled. Thank you so much for your time and efforts!

автор: Jiwan

31 июля 2020 г.

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

автор: Sumit K

30 мая 2020 г.

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

Great Experience, i learned a lot. !!!

автор: Tarek A Z

16 июня 2020 г.

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

автор: PRIYANKA N

9 июня 2020 г.

The course was so amazing.

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

автор: Faizan A B F

23 мая 2020 г.

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

автор: Koustubh P

9 июля 2020 г.

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

автор: SHIBU M

8 авг. 2020 г.

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

автор: Adarsh S

21 мая 2020 г.

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

Course instructor was great!

автор: Suhaimi C

7 февр. 2021 г.

Great Course. Highly recommend it to practice your machine learning skill and understanding.

автор: Ling Z P

26 июня 2020 г.

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

автор: Shreya S

9 июня 2020 г.

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

автор: Aastha A

9 июня 2020 г.

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

автор: AARUSH K 1

23 сент. 2020 г.

Very exciting project and instructor is also very good,and explained very well everything.

автор: Muthukuda A R L S

16 июня 2020 г.

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