This is honestly one of the best courses I've ever done. I had completed the Tensorflow in Practise specialization by deeplearning.ai a couple of months back and took up this course as a refresher but this ended up being so much more! The lecture videos are top quality and explain the basics really well and the coding tutorial videos helped me get some much-needed practice. This course stays true to its name and covers important topics like designing custom models using the Model Subclassing API and using custom training loops. The assignments are very relevant to the course content and the capstone project, when finished, leaves you with a real sense of accomplishment and pride!

The lectures are clear and the coding assignments are very relevant and practical. The final project is complex but it is very rewarding once you complete it.

This is the best TF course in Coursera. The 4th week for Model subclassing and custom training loops is really informative and fantastic, which gives us full flexibility on TF model construction and training process.

Very well organized tour through Tensorflow 2 API, I learned a lot and enjoyed the course

The gap between the programming assignments and the cap stone projects is to wide

In short, take this course if you want a challenging course where you can learn TensorFlow 2 in depth.

I will add to my review on the first course of the specialization.Kevin and the GTAs do a brilliant job at mainting the assignments and autograders and the learning community is really helpful too in case you get stuck in some part of the assignment or the capstone project. Highly recommended!

great course

This class is very good , I learned enough knowledge of tensorflow ,such as how to use tf.data ,how to embedding, how to do tokenlization, also I learned how to build customized tensorflow models

It just the last assignment of making a translation model, I had no idea where to start. It would be nicer to include a video to explaining the encoder and decoder mechanism

Excellent course! 100% recommended for anyone looking for more advanced TensorFlow knowledge.

Excellent course!

Overall, an exceptional and highly relevant course. I would have given it five stars, however some instructions on the capstone project were too vague, causing the project to take much more time to complete than is really necessary. Also, it appears that correctly completed neural network translators don't appear to produce very good translations, at least in the form we were asked to design, and I think there should be some comment about that from the instructor. Is it because the embeddings we were given were not that great? Was it because the network we designed was not deep enough to be effective, or was our custom training loop not well conceived? Thank you for developing and presenting this course. I especially appreciated Dr. Webster's clear and concise lecture videos. Overall, I thought the course nicely dovetailed with the two Andrew Ng courses I previously completed on Machine Learning and Deep Learning (with TensorFlow 1). This course helped me become a better programmer and was worth the effort I had to invest in it. Hopefully I will complete the final course in the specialization very soon, and launch my new career in AI software engineering!

I really like the course. It is repeated what I already knew but gave a lot of insight in customization. The high level course video are great they show the essence in a very clear and consice manner. I hope there are more courses like this coming. For me this was one of the best online courses I have done!!

Overall, not bad. But Capstone contains too much knowledge points that were taught in the previous labs and video lectures. A little stretch from the taught material is training and exercising, too much stretch is kind of waste of time. I took 4 weeks part timely to complete the Capstone project, which supposed to take an hour. And in general, I know my progress in other courses. So, I know this is out of the norm

Best (and also hardest) coursera course I've completed so far. I particularly appreciate how the course let one get to grips with the TF documentation: when I started this course, that documentation was pretty opaque and incomprehensible to me, but now I find it a very valuable resource. The forums were great for clearing up problems, though sometimes I had to look very hard. The capstone project took me about twice as long as the suggested time, but then, my python skills ain't the best, as yet.

This course is very challenging, as require concrete understanding on tensorflow to conduct the whole project

Very useful course!!! Thanks!

Scope for improvement, for the RNN, LSTM, and Bi Directional layers.

Learnt so much doing this course. It had the right level of challenge if you have background knowledge of basic TensorFlow and ML. The assignments followed on logically from the weekly exercises and tutorials and the capstone project for RNN encoder-decoder required additional problem solving (I recommend reading this additional resource https://machinelearningmastery.com/return-sequences-and-return-states-for-lstms-in-keras/).

Kevin Webster and the programming tutorials teachers were clear and brilliant as usual. Only point to improve is that the text on the programming tutorial videos was very small to read.

I was concerned that noone would review my capstone project as I am doing this course 2 years after it was released but it was reviewed within 5 days -- thank you so much fellow learners.

Such a great course! The content of the videos is concise and relevant. That said, it is always nice to take a look at the core of some topics if you want to have a better comprehension of them. I had to dedicate quite some time reading about RNNs to understand and not just imitate. Some labs, especially on week 3 might be better if they include some extra explanation of some of the code.

The capstone project is somewhat challenging but doable, and it's very rewarding once you complete it!