8 mars 2019
Good intro course, but google colab assignments need to be improved. And submitting a jupyter notebook was much more easier, why would I want to login to my google account to be a part of this course?
13 août 2019
Great course to get started with building Convolutional Neural Networks in Keras for building Image Classifiers. This is probably the best way to get beginners into Deep Learning for Computer Vision.
par Matthew R•
13 déc. 2020
Really superficial overview of tensorflow and deep learning. Very few concepts were explained in any real depth.
par Suraj R•
18 juil. 2019
Resources shown in the video were not included as web links, so the course couldn't be completed
par Rudrani G•
25 août 2019
A little too complex for beginners. Content must be explained from a novice point of view
par John M•
5 juil. 2020
Some reading exercises had missing links and some code used a deprecated function.
par Gautam K•
16 janv. 2022
Not a great experience with the assignments, especially the last one.
14 juil. 2019
This course teach how to use Keras more than using Tensorflow
par 41_AI&ML_Mehul S•
29 mars 2022
Very Easy Course. A basic course marked as intermediate
par Francisco R•
23 avr. 2019
It´s well explained but way too basic and short.
par Xixi W•
10 août 2019
这课挺水的， 不如 deep learning specialization多矣。
par Alejandro D•
20 août 2019
notebooks need work from the instructors
par Deleted A•
30 juil. 2019
Course was not rigorous enough
par Reinier V•
12 janv. 2021
par Peter C•
11 août 2019
par Adam F•
1 nov. 2021
This specialization is false advertising. It does NOT prepare you for the Tensorflow certification exam. It’s especially disappointing after taking the fantastic specialization by Andrew Ng, and makes this specialization feel like a cheap cash grab by Coursera and DeepLearning.ai. This series of courses fails to prepare you for three reasons:
1 – The certification exam is done on whatever is the current version of Tensorflow (v2.6 as of writing). You can’t expect a specialization like this to update every minor release, but much of the coding is still on the v1.X version!
2 – The certification exam requires you to work in the PyCharm IDE. The IDE doesn’t even get a mention in this specialization and it is all done through Google Colab.
3 – The material is covered at a very superficial level. I was hoping to walk out of it feeling confident in using Tensorflow on novel problems, but I’ve barely learned anything about Tensorflow that I didn’t already get from Andrew Ng’s specialization. There’re a few minutes of lectures (some weeks less than 10 minutes). The programming assignments are either pathetically easy, or lack any guidance on what to do (seriously sometimes there’s no instructions at all, you have to guess what to do by the variable names), or both.
Save your time and money and go elsewhere to learn Tensorflow.
par Maciej D•
12 août 2021
This course is FULL of errors (both in code and math), inconsistencies and wrong explanations. I tried to document them, but I just gave up, because it is so many of them... For example the math which explains multiclass classification (Week 2 Video “Coding a Computer Vision Neural Network”) is wrong – the output of multiclass classification should be pseudoprobabilities, not numbers ranging 1 to 9… There are also unsolved problems reported in GitHub (https://github.com/lmoroney/dlaicourse). It seems like they really don’t care about correctness, completeness and quality of this course… If you want to learn TensorFlow I highly discourage to use this course - you will just learn wrong things and would have to unlearn them later... Also graded exercises are in TensorFlow 1.x and materials are prepared for TensorFlow 2.x which means that sometimes the code from materials does not work in graded exec, eg. logs.get('accuracy') does not work in tf 1.x and you need to use logs.get('acc'). I did this course only to get some practice and pass TensorFlow exam, because I'm academic who works with PyTorch.
par Yoni K•
1 oct. 2019
First of all, it's an introduction to Keras and not Tensorflow.
Secondly, the explanations the author gives are lacking/misleading.
For example,in week one the net didn't learn exactly the hypothesis 2x-1 for other reasons than the ones he mentioned (oh,and the net did not give some kind of a probabilistic interpretation to the data...).
I am not sure why Andrew NG (who is the best instructor in the world to my mind) allowed this kind of instructor to be branded as deeplearning.ai.
par Anthony G•
4 déc. 2020
This course claims to be over 28 hours, however, I was able to finish it (watching every video, reading every bit of text, doing every exercise) in less than 6 hours. The lab work is a complete copy-and-paste of the examples covered in the course. If you want to "buy a credential" take this course, but if you want to actually learn anything, take another course.
17 janv. 2022
This is a poor course. The course assignments often fail for mysterious reasons (Grader timed out, Grader ran out of memory), and the course points to outside resources more than its own explanation.
I found the explanation deeply lacking. I would suggest not taking this course, and I will not be taking the remaining courses in this specialization.
par Andrew N H•
15 janv. 2021
the instructor did not give us enough explanation for the code written, it is just reading it. many things he added in his code does not make sense for the beginners like me. in addition that he said that it is out of the scope of the course. so why did you add it in your code. i feel the instructor should explain things more than that
par Mayuran S•
13 août 2019
This course does not go very much into detail and way too much time is given for easy exercises and homework. The homework contains a lot of bugs, which need to be fixed since students waste a lot of time debugging errors which are not due to their fault. Furthermore, the homework is just about copying the code given in the videos.
par Timofey G•
5 août 2019
The videos don't contain much usefull information, but only a demonstration of the most basic concepts of tensorflow. Practical assignments does not aim at teaching you any skills, but copying code from one notebook to another. And after this course I actually have some concerns about the author qualification on the subject.
par Kanak B•
1 juil. 2020
There's barely enough material to qualify it as a course. Each week's videos combined are less than 30 minutes. They just link you to more resources such as Andrew Ng's Deep Learning course material. It took me less than 3 hours to finish this course. There's nothing of substance in this course. A disappointment.
par Juan L L•
14 mars 2020
Vague, you should really have prior knowledge of deep learning, this specialization won't teach you anything in detail. The specialization focuses on just a few examples of not TensorFlow, but of Keras. You will have experience in solving almost already solved, arbitrary problems.
par Yunus Y•
25 déc. 2020
Unexpectedly from coursera and sadly, there are too many abandoned courses and these courses are a few of them. Outdated datasets, outdated codes, students trying to help each other but many people don't understand what's happening here and there are no mentors to help along.
par Maged A•
7 nov. 2020
Course material is outdated. There is many mismatches between the videos and the notebooks. Material is not updated for smooth progress. Many sections are talking about examples and no links for them. It seems that no one reviewed the course content since it was launched.