Excellent introduction to the mechanics of Neural Networks in general, and the Keras application specifically. Alec is an outstanding teacher, I always appreciate his knowledge and enthusiasm.
Interesting course. Forward propagation, gradient descent, backward propagation, the vanishing gradient problem, (+ Regression, Classification, and CNN with Keras) explained clearly.
by Xiaoer H•
The course contents are not in-depth enough. The server for Jupyter notebook running is way too slow. Besides, the peer review homework is not that good, because some people didn't read through the questions carefully enough, and they misunderstood the questions themselves and could not give fair enough grades to peers. If the final assignment can be made to auto-grading one, it would be much better (we can set the same random seed)
I have experience of Deep Learning, so I am able to walk through this Lession quickly. The main focus is on Capstone Project, and I have learned something on it. To be honest, this lession is very elementary. I suggest to introduce more Deep Learning models and approachs in this lesson.
by Sander v d O•
This is a great course. The lectures are boiled down to the essence of neural networks using Keras. I give four stars instead of five stars, because the IBM labs environment that the course uses was quite slow and buggy, so I ended up doing the exercises in Google Colab.
by Adriano S•
The Course is basic but interesting. I missed an exercise on backpropagation with the same explanatory level that it had for forward propagation. The last activity needs to be reviewed because it is confusing.
by Deleted A•
Nice overview. The coding exercises could be deeper, and in the second half of the course lose any depth at all. Understandable for such a short course, but still felt like a missed opportunity.
by Aaqib W S•
A good course. Could be better if it was explained how to select the optimal number of layers and nodes. This was not covered and explained anywhere. Overall it was good.
by Rohit S•
I took this course for understanding the TensorFlow properly. Now I am in the situation to understand all the frameworks. Thanks a lot for providing me this free course
by Benhur O•
Good practical examples for ANN. It could be improved the theoretical part and compare better the architecture of the networks with the algorithms and code for Keras
by Mohamed A A•
A good introductory course, well suited for beginners looking for general information about neural networks and deep learning, with good practice exercises.
by Lete N•
Good intro to the subject. The instructor could have done examples using other neural networks like RNN and autoencoders. It was a fantastic intro
by Rashmin D•
It is a good insight for someone to know and understand Deep learning. And exams and projects make sure students learn and practice new concepts.
In-depth concept-analysis is required. Good for people who know the theory and want to learn and revise its implementation in Python.
by Julius M•
This course gives intro to the beginner who start learning the concept of deep learning.... It a good and content are good as well
Very good. I found this course very usefull to start learning more deeping in this technology. For sure I'll recomend it!
by Emanuel N•
Muy basico, pero contenido estuve bien, los temas fueron bien explicados
by Jay P•
Excellent course that is very well done. Final project was super hard.
by mallesh v s•
Very Good Course to begin, explanations are clear on most of topics
by Nehal B•
It provides good basic understing of deep learning using Keras!
by Vishwanathan C•
Very nice and concise introduction to Keras and Deep Learning.
by Vijander S•
some interdisciplinary data set examples should be included
by Sarah T•
A course which gives basic understanding of concepts.
by J K•
excellent course and but need some advanced content
by TJ G•
Great starter. Could do with more practice labs.
by Udaykumar A•
Good course which provides practical exposure
Not too bad a course and the pace was right.