Learner Reviews & Feedback for Creating Multi Task Models With Keras by Coursera Project Network
About the Course
functional API to create a multi output model which will be trained to learn two different labels given the same input example. The model will
have one input but two outputs. A few of the shallow layers will be shared between the two outputs, you will also use a ResNet style skip
connection in the model. If you are familiar with Keras, you have probably come across examples of models that are trained to perform
multiple tasks. For example, an object detection model where a CNN is trained to find all class instances in the input images a...
Top reviews
GP
Jul 1, 2021
This course is pretty good, that I learned many concepts in one hour. The instructor too very good that his way of explanation made me to understand it quickly.
KK
Feb 25, 2023
Fantastic course and very easy to follow on implementing multi-task learning on the MNIST dataset. Thank you very much!
1 - 12 of 12 Reviews for Creating Multi Task Models With Keras
By GOSU P
•Jul 1, 2021
This course is pretty good, that I learned many concepts in one hour. The instructor too very good that his way of explanation made me to understand it quickly.
By Kamalpreet K
•Feb 25, 2023
Fantastic course and very easy to follow on implementing multi-task learning on the MNIST dataset. Thank you very much!
By Mohd. F I S
•May 15, 2021
Amit is awesome. You are one the best instructors/teachers , I have ever seen in my life.
By Chow K M
•Feb 6, 2022
An useful practice and review of keras functional api.
By Kenneth N
•Jun 30, 2022
exceptional and very clear. great project
By Shadi Q
•Jan 20, 2023
Small project, great content!
By Shahid N K
•Apr 22, 2022
Excellent guided project
By Oshan J
•Jan 6, 2022
extremely valueble
By Tưởng N H
•Jun 28, 2021
great course
By Sanjay K
•Feb 23, 2021
The project was simple yet provided the core idea of going for multitask model with an interesting use-case.
By Jing Z
•Feb 18, 2021
Great lesson!
By MBT18CS085 N S
•Jun 10, 2022
keras