Opiniones y comentarios de aprendices correspondientes a Introduction to TensorFlow for Artificial Intelligence, Machine Learning, and Deep Learning por parte de deeplearning.ai

This is fantastic stuff, made simple if you have done earlier course of Deep Learning from Dr. Ng this is at another level, I feel little confident that I may be able to code without copy pasting.. hopefully the next course in the series gets introduced serious stuff..

Good course which gives the brief explination on how to use the TensorFlow framework to solve many computer vision problems. This course is designed to such that the beginner too will feel more confident understanding the details of the machine learning techniques.

Overall, pretty good, clear information. The submissions were a bit annoying because of bugs with the system, but that wasn't anything to do with the course content.

Some of the "graded" exercises could have been a bit more thought-provoking and less "copy & paste".

This course actually gives you hands-on coding deep neural networks starting from very basic ANN to image classifier. The explanation is easy to understand and is more focused over practical part which is very important. Overall the course is an excellent starter.

Hello ,

This was very helpful , I gained some new information.

I can not believe that I finally used the famous tensorflow library , and this is my first time to do picture classification.

This course leaved me with some questions that I will try to research.

Thanks for the course! This course pretty much starts from where I left off i.e. Machine learning course from Andrew NG. And, I am happy using TensorFlow which saves a lot of time to experiment and concentrate on the problem at stake than the program itself!

I like courses that are longer and more in depth such as the first specialization of deeplearning.ai, I just could not continue that one because financial help always got me financed the first course which I had completed and cannot pay for the other ones

Nice introduction. Tests are too easy. Exercices are easy too, but still is fine, rather I prefer them to be more challenging (like: 'try to play with number of epochs and other parameter to achieve 99% accuracy for example ' and do not guide to much).

This course was a little too basic and introductory, personally. But the course structure really makes up for it. It is better suited for someone who is new into this field. Since I had half a year's experience in PyTorch, this course felt too simple.

I loved the fact that it was more hands-on than theoretical. Although I did expect some more explanations on some parts.. but the suggested links were good enough for those parts.. Overall, I loved it. Lawrence is really good at what he's doing.

Should have provided more explanation about the assignments. The explanation videos about the topics are no longer than 4 minutes. You should know some of the DNN concepts, then you can understands the assignments in depth and more clearly.

Not being able to run the notebooks on Coursera was frustrating. Fortunately, running them on colab wasn't difficult - just an unnecessary impediment.

Was nice to see some of the more abstract deep learning terms be put to use fairly easily.

May be provide resources to learn some senior grammar knowledge for python, because basic knowledge for python does guarantee we could understand the code perfectly, but simply remember its form in case of a particular complex line of code.

I had a background of Andrew Ng's Machine Learning Course so i did not really have any difficulties with it. However, a bit more detail on conv nets' theory will make this course much better. Still, I loved this. Thank you deeplearning.ai!

Good course, somewhat easy, but I anticipate a lot more new and interesting and useful stuff in the remaining sessions yet to be offered. It would be good to point out what is now Tensorflow 2.0. I anxiously await the new material. Thanks!

Great course, excellent contents. I would have loved more smooth intro about the generator as I found we suddenly went to talking about this generator without prior introduction. To be honest, I still cant see the value of this generator!

Good introduction to TensorFlow, but that is all there is.

Don't expect to gain any understanding in how neural networks are and work from here. It is only about learning the TF API.

I think the title is a little misleading in that sense.

Very conceptual course, with few exercises to help you learning how to build a basic convoluted neural network to a dataset of images. I enjoyed it, also because it provides many sources to use if you want to dive deeper on your own.

I learnt PyTorch prior to TensorFlow. Still found this course is very helpful. Thanks to the instructors. The only thing is, I wish all the reading links could be listed down on one page, and all the notebook links arranged together.

Laurence is an expert in this field. The material covered in this course is relatively basic, but I think it is a good introductory course for TensorFlow. I was expecting more / elaborate material for the graded assignments, though.

I took this course for the more low-level API in TensorFlow since I already had experience with Keras. But it was still a fun course to watch and an excellent start for people who are just beginning their journey in Deep Learning.

The week four programming exercise needs some improvements. I can not unzip the data, so I had to download this exercise and finished it in local environment. Finally, I hope some videos can have Chinese subtitle in the future.

This one is basically an intro on how to use tensor flow apis to build neural networks. it is very useful to learn how to use these APIs and some Python code. I'm looking forward to learn more about CNNs in the next course.

very practical courses with examples. May address some knowledge on NN architecture design, such as why place an additional flatten layer before the final layer. Some cases, we didn't need such layer and the reason why?

Probably one of the best course!! I think the team needs to fix some parts, where the instructions aren't clear. Honestly, it is amazing that we can create a simple machine learning model with just a few lines of code!!