糖心vlog官网观看

i recommend the course for anyone want to get solid foundation in TensorFlow as beginner, also capstone project cover all the content you learn in the course.

This course had a good balance between the application-specific elements and the broader ML discipline. Good teaching and materials.

Although there is lacking feedback on instructor team on the forum, I would highly recommend the course in terms of the content.

Really amazing experience with this course perfect start after knowing the mathematical concepts of how nn works

Very good for those people who have knowledge of deep learning and want a hands-on in TensorFlow 2

Great and clearly taught course for anyone with basic knowledge of Python and neural networks.

Well defined course. I got a very good experience. well planned handson session. Thank You

Provides detailed coverage of tensorflow 2's fundamentals. Thoroughly enjoyed the course.

An excellent course for those who want to learn how to implement tensorflow2.0

The best course if you want to get started with Tensorflow 2.0

It provides a systematic way for me to learn TensorFlow 2.

It is an excellent course for beginners in Tensorflow

Excellent course for getting started with Tensorflow.

Loved the course. Really practical and hands-on.

Thanks for all, really useful course!

Very clear and well organized.

Awesome course. Learnt a lot

Great overview of TF2

Great course.

Good beginner

FYI This uses tensorflow 2.0 would be nice to have an updated version for 2.4>

The perfect course to follow up the Deep Learning Specialization. I left that specialization feeling like I had an acceptable academic understanding of deep learning, but that I would be unable to apply it in practice. This course was great for solidifying that pragmatic component.

I read some of the most helpful comments before starting and one of the biggest frustrations was the auto-grader failing. That was not my experience at all. As of this post (5/2021) the grading system worked completely fine for me via 糖心vlog官网观看's notebook system.

A concern among other TF specializations was that they did not provide any information that could not be gained outside the doc examples. For this first course, at least, I found the material well exceeded the explanations in the TensorFlow/Keras docs in terms of quality. The labs were very thoughtfully structured and provided the right amount of application to cement the concepts mentally.

tldr found this course to be very worth the time and money

This is just a wonderful course!

Previously I've taken well-kown Machine Learning course and Deep Learning specialization by Andrew Ng. After completing these courses, I had the feeling that I had received a good knowledge of the theoretical aspects of Machine and Deep Learning, but I had no understanding of how to make some even simple models from start to finish (I am not criticizing these courses, most likely the problem is in me).

And this course was a real godsend for me. This course is completely dedicated to practice, this is exactly what I needed. The information presented in it is absolutely clear and contains everything you need to complete programming tasks and to start the independent development of simple models in tensorflow.

No doubt, 5 stars!

Beginning is too basic for me but I like this course because it's a well structured tutorial-like course if you want to learn Tensorflow. First course is about Sequential API, second about Functional and Subclass API and the last about Tensorflow probability library.

It's not going to teach you basic concepts of deep learning like deeplearning.ai specialization but this specialization (its first two courses) is significantly better in explaining how to actually code with Tensorflow - it introduces very early the callbacks and optimization techniques directly into code labs in a way you can see and understand what happens.

I really liked this course. The pace is very good. The focus is also great.

The final project (Capstone Project) is really good practice, I'm not super experienced in ML so doing a kind of "real world hands on project" fell great, even if I spent a lot of time doing it (I made an initial wrong assumption about the data structure which made the model trainings take forever).

You are going to need to know about Python and Numpy, maybe a little Pandas too.

My only constructive criticism would be that it would be great if you got a good mic鈥� these makes videos much more pleasurable. Audio isn't great.