A good introduction to AI networks in raw Tensorflow without heavy reliance on Keras, definitively matched my expectations!

The LSTM model and Restricted Boltzmann Machine explanations were quite hard to follow and I had to resort to other websites to learn more about the basics of these topics...

Otherwise, very interesting and I would definitively recommend it!!

Very interesting material, and easy to follow along. The notebooks are a great resource. I am glad to have been introduced to these concepts. However, I felt this course was too easy and it did not encourage the student to complete projects or any independent work. In any case, this course was worth taking.

I liked the course; however, there was no sound or transcripts for the last week of the course. This required me to research all the topics that I saw on the screen. Still a good learning experience but put more responsibility on me to learn the topics.

This course was an excellent balance of theory and hands-on practice. The labs was an excellent environment to practice what we were introduced in the videos. Highly recommend for anyone looking to deepen their skills and knowledge in Deep learning!

Building Deep Learning Models with TensorFlow Has a lot of math explanation and good visuals, but lacks training cells for the labs and there are no questions during the videos. If you want to practice Tensorflow, you´ll have to do it on your own.

Interesting course but I wish there were more opportunities to add code myself or even a proper task. I was sad not to have videos from Romeo. However, I thought that the explanations of the different deep learning models were very clear.

Quite a basic course, you don't get to learn much of tensorflow. This is an introduction to some deep learning models, the content is clear and the course it is well-structured, but it does not go very much in depth.

Excellent notebooks. I don't give 5 stars because the quality of videos could be improved and the quizzes could be made tougher. It is easy to pass the class with a superficial understanding of concepts.

Nice course to introduce you to more advanced neural network algorithms, I wish the evaluations were more challenging and based on practical exercises... there is no final assignment either.

It would have been nice if the video tutorials would explain the code section as well, and if there would have been some in-depth teaching of the code part. But this course did benefit.

Videos are good, but the code is more complex than other courses and it needs better description of what is happening, or less complicated code

Good an simple videos to understand the concept. The notebooks are very detailed and give a second layer of knowledge with practical example

Videos are good. Lab notebooks are a bit stale (still on tensorflow 2.2), so there are few wrinkles in getting them to work.

The course concepts are not in-depth enough, and the server for Jupyter notebook running is way too slow...

I expected some more explaination for the concepts. However from tensorflow website, more could be learnt.

The coding part was hard to understand. If that part could also be covered in videos as a tutorial.

Great introduction to unsupervised learning. However its an easy course with not much to offer

challenging but i wish the quiz questions were more useful in testing our understanding.

Missing more theory in the course, some labs is not working well. Need review all labs.

The course is fine, but I don't know why IBM put reinforcement learning here.

It would be grate that the examples have been updated to the TF 2.0 version.

i loved it. I have an undertsanding of different deep learning models

Was a really fun course, but the final assignments were very lengthy.

Good material but almost all the labs are too slow to run properly

Good introduction to Deep Learning Models with Tensorflow