MM
Jan 24, 2021
I already knew the subject, so I was able to go fast, but I really loved the completeness of this course, the approach, the tests, and the capstone project. Basically everything. Very good indeed!
AA
Mar 17, 2021
Provided clear and useful insight into TensorFlow 2. Before the course I had read many of the TF2 guides and tutorials. This course helped solidify my understanding of core TF concepts.
创建者 Islomjon S
•Dec 4, 2020
It was incredible experience to study TF 2 with this course. Progressively, we studied each component of Tensorflow to build eloquent ANNs. However, it was very shallow application of Tensorflow in just using CNN (which they explained 100%), it would be very good if they also showed some other architectures too.
创建者 Andrew H N
•Jun 24, 2021
Getting Started with TensorFlow 2 was a great course -- focused, relevant, professional, and highly value-added -- thank you, Dr. Kevin Webster, and the Graduate Teaching Assistants, for presenting it! I am looking forward to completing the next course in this Coursera specialization! Best Regards, Andrew
创建者 Woosung K
•May 5, 2021
You need to have some experience in numpy before taking this course. In particular data preprocessing is challenging without such experience, I would say. Other than that, everything is excellent. Especially I like that I can run codes using CoLab/Jupyter notebook without installing all dependencies.
创建者 Goh K L
•Dec 13, 2021
This course is a good complement to the courses offered by Deeplearning.ai in terms of focusing on the basic neural network coding. I like that the exercises in the Jupyter notebooks were left empty for students to type the codes. This encourages the students to pay attention the tutorial videos.
创建者 Akash M
•Sep 23, 2020
Intended for intermediate level students, is seriously one of the best courses with the right amount of rigour and testing. Thorough coverage of TF2; seriously would love more of such courses (apart from the specialisation) from Imperial College in this ever expanding field!
创建者 Arish A
•Jun 10, 2021
Great course, i loved the fact that instructors were showing the use of Docs and the assignments in the course were nice. I like that the couse assumes a prior knowledge of Deeplearning and does not repeat them in great details here.
创建者 Yevhen D
•Feb 27, 2021
I recommend this course:
1) A lot of practices: assignments, notebooks, capstone project.
2) Theory videos are very clear and compact.
3) Authors don't try to teach you ML in 5 weeks, but instead require ML knowledge and focus on TF.
创建者 David H
•Apr 6, 2022
Excellent introduction to Sequential models in Tensorflow 2, very clearly presented with well-designed tutorials, and covering a lot of useful material. Assumes a little (but only a little) previous knowledge of neural networks.
创建者 Juan C S S
•May 26, 2022
Such an amazing course! Explanations are concise and clear, and the labs are always a good opportunity to apply the new content. Weekly and final projects are great, and actually have a real application.
Great teachers as well!
创建者 Gael H
•Apr 5, 2022
Excellent course along with course#2. Very clear and useful explanations about using Tensorflow in a professional settings. These courses are real lifesavers given how terrible is Tensorflow documentation.
创建者 Thales G
•Apr 7, 2021
Good course. Short and very practical. It is not a basic course, as you need to know some aspects of Machine learning and Deep Learning. It opened my mind for other possibilities of use of neural networks.
创建者 mausci71
•Jan 25, 2021
I already knew the subject, so I was able to go fast, but I really loved the completeness of this course, the approach, the tests, and the capstone project. Basically everything. Very good indeed!
创建者 Rob S
•Oct 22, 2020
Excellent course! The project assignment provides a very good way to self-assess and see whether you really have understood the course material. It's a strong recommendation from me!
创建者 Anudeep D
•Dec 22, 2020
One of the best courses that i have taken on coursera. Clearly explanation of concepts and very good labs which give data scientist clear path to train models using tensorflow 2
创建者 Hazem A
•Nov 25, 2020
Excellent Course .. One of the best for practicing Tensorflow . Great content and well designed assignments ... GTA did a good job though sometimes the accent is not very clear
创建者 Fabio K
•Nov 5, 2020
Very good training. I certainly learned a lot and am getting used to this framework already. Some theoretical background in ML is highly recommended before taking this course.
创建者 Gergely S
•Mar 14, 2021
Working along with University PhD students is very helpful! Also, the explanations from Kevin are very detailed with good visualization (highlighted source code lines).
创建者 Arash J
•Dec 10, 2020
it is an awesome course for anyone with knowledge of deep learning to learn tensorflow. looking forward for other courses in the specialization to learn more.
创建者 Fortià V
•May 11, 2021
This is a great course to gain experience using tensorflow 2 and also to reinforce the concepts of Convolutional Neural Networks. I strongly recommend it.
创建者 Ricardo D
•Feb 23, 2021
Very good course -- explained the basics of tensorflow 2; very confident at this point that I can start developing my own tensorflow/keras applications.
创建者 Fernando S
•Nov 13, 2020
Awesome course, the best basic Keras course at Coursera, it should be more promoted, after so much time using TensorFlow, I've just found it now.
创建者 Ton P
•Apr 12, 2021
Very nice course, especially when you are already familiar with the deep learning concepts and just want to know how to code them in Tensorflow.
创建者 Ajay A
•Nov 22, 2021
Indeed intermediate level course. Useful course. Well designed, focussed, clutter free, comprehensive. Rare to find such course on Coursera.
创建者 LRAV
•Oct 27, 2020
This course is terrific! All you need to start coding almost any DL model. Really good to get yourself comfortable with tensorflow.
创建者 Shine B
•Jan 10, 2021
A well structured and useful course. I definitely recommend it to anyone who is searching for a solid introduction to TensorFlow.