Very good course to give you deep insight about how to enhance your algorithm and neural network and improve its accuracy. Also teaches you Tensorflow. Highly recommend especially after the 1st course
Thank you Andrew!! I know start to use Tensorflow, however, this tool is not well for a research goal. Maybe, pytorch could be considered in the future!! And let us know how to use pytorch in Windows.
創建者 Tom T•
Overall, it's pretty good. I did have a problem understanding some of the facts being communicated about gamma and beta in batch norm. Also, I think there is a problem with the last notebook. My cost did not go down as fast.
創建者 Teddy G•
I think the last subject, the "gradient checking" looks a bit not connected to the begining of the week 2 course, it may be only me, so I will go over it again and try to understand its relevancy to the rest of week 2.
創建者 Tim H•
Good choice of topics to cover. I think the central idea of some of the videos could have been summarized much more quickly, in a minute or two, with the rest of the time spent going into more depth if the student needs it.
創建者 Mukesh K•
The content of the Course is very precise and assignment truly reflect what is been taught in the lectures. Explanation and presentation of algorithms are what I like the most. Assignment were very engaging and interesting.
創建者 Jie Y•
The class should include more introduction on the current ml frameworks such as tensor flow etc. Possibly it should include one more project for the ml framework. Hope to give students more experience on the ml frameworks.
創建者 Deva C R M•
Good and detailed information on how to tune parameters, optimization techniques and regularization. I'm confident that this course learning will help me in training NN to better convergence in a shorter time than earlier.
創建者 Karl S•
I would have liked more details on the math. Furthermore, I think that the discussion of TensorFlow was a bit too short. Although I was able to do the assignment I have not yet developed an understanding of TensorFlow.
創建者 Julien B•
Excellent. Mon regret est que l'exercice final ne mette pas en oeuvre le tuning des hyperparamètres sur un jeu de cross validation. Un exercice supplémentaire avec TensorFlow ou Keras sur cette notion aurait été un plus.
創建者 wilfried l•
As usual, it is very good from theory point of view. Practical examples are also really interesting.
Do not expect to be autonomous after the course, as you won't be able to use Tensorflow or Keras alone.
創建者 Gil F•
I'd make the tesnsorflow section a separate week with much more elaboration, the first time (in both course 1 and course 2) I felt a subject was lacking information. It's mostly noticeable in the programming assignment.
創建者 Marc D•
The course really takes the student by the hand through the exercises. The disadvantage is that it is not really necessary to understand what you are doing. Just follow the guidance. But on the whole really satisfactory
創建者 Heung K L C•
Very exciting and interesting course overall but the programming assignment with Tensorflow was not practical in my opinion. Instead having practical experience building NN with Keras might have been the better choice.
創建者 Nikolay K•
Generally the course is very good! I liked that I could manually implement the steps of hyperparameters tuning. I wish there was a bit less boilerplate code. Implementing everything from scratch would be more valuable!
創建者 Mark H•
Could be Greatly improved by having us build a NN using previous learning's with the only change being use of SoftMax for Cost. Then have us use TF to do the same and compare the code effort, and the results 1-to-1...
創建者 Gabriel R•
Muy buen curso! Me hubiese gustado que se desarrolle un poco más TensorFlow. No me quedo claro por ejemplo, cuándo hay que inicializar variables, si es realmente necesario definir las constantes con tf.constant, etc.
創建者 Raúl A d Á•
The explanations are amazing. I do not qualify with 5 stars as I think that practice can be structured in a better way. If the practice is done after each module in each 'week' it would help to retain main concepts.
創建者 Ralf S•
Good course overall. but labs could be expanded. Don't know if the Coursera platform supports it, but labs between lectures about different topics would be nice instead of having all practical exercises at the end.
創建者 Christoph D•
Nice course, as always!
But I think the hyperparameter tuning methods are hopelessly outdated / missing the most promising current developments. A pity since this is such a central part of the actual work with DNNs!
創建者 Yuvini D S•
You can get a better insight as to how to improve neural networks that go beyond the fundamentals. The quizzes and assignments helps you get a hands-on experience of the theoretical material covered in the course.
創建者 Oriel B•
I enjoy the course a lot!
for tensor flow - I am not sure if its me or the course - but I need much more training to start thinking the tensor flow way. maybe i will practice more on real work cases.
創建者 Craig M•
You've learned deep neural nets but on the first problem you apply them to they seem to not work or learn to slowly. Don't panic, all you may need is a little fine-tuning, that is what this course will teach you.
創建者 Joakim P H•
After this second course you will be able to start build things using Tensorflow. Really great to see how good this course is structured. Things from course one is comming back making it easy to grasp new content.
創建者 Gemeng Z•
Overall, the course is interesting and introduces systematically technical details. There are still some confusing part in the assignment. For example, the direction in the last assignment is kind of misleading.
創建者 Amir H•
The explanation and examples are very informative throughout the course. The quizzes and the assignments are highly related to the topics covered in the videos which provide a solid understanding of the course.
創建者 Luca V•
Some very interesting consideration, though I would have liked a section about reproducibility and randomisation (including for GPU trainining), though I understand that this is framework and language dependent