Sep 12, 2019
great introductory stuff, great way to keep in touch with tensorflow's new tools, and the instructor is absolutely phenomenal. love the enthusiasm and the interactions with andrew are a joy to watch.
Sep 14, 2019
An excellent course by Laurence Moroney on explaining how ConvNets are prepared using Tensorflow. A really good strategy to have the programming exercises on Google Colab to speed up the processing.
교육 기관: Nick A•
May 08, 2019
This course significantly lacks depth. The topic is covered at a very high-level and represents only a lightweight introduction. You will not gain any insights into the challenges that someone might face using CNNs on Tensorflow in a real-world scenario.
This course does not compare to the kind of insights that you learn from the other courses taught by Andrew Ng.
There are no graded programming assignments to validate what you have learned. The exercises that are provided are very simplistic.
교육 기관: Имангулов А Б•
Jul 03, 2019
You may look at it as a set of use-cases on how to work with particular types of .ipynb notebooks or how to structure your code, but, unfortunately, lectures are useless and tasks are mechanical rather than challenging.
교육 기관: Irina G•
Aug 02, 2019
I think I knew more about CNN before this course.
교육 기관: Asad K•
Jul 04, 2019
This is the second course of the specialization and still I feel like I haven't been introduced to anything beyond the free tutorials available on tensorflow website. So far the specialization has also been only focused on the keras api of tensorflow which makes me feel that perhaps the name of this specialization has been poorly chosen (perhaps it should be 'Keras in Practice Specialization'). On the positive side, the instructor is eloquent and the learning material is presented in a well and orderly fashion (ignoring some minor cases of redundancy in notebooks; basically copy pasting the whole notebook several times just to introduce a few lines of new code).
교육 기관: Romilly C•
May 15, 2019
Excellent material superbly presented by world-class experts.
Sorry if this sounds sycophantic, but this series contains some of the best courses I've encountered in50+ years of learning.
교육 기관: jbene m•
Jul 30, 2019
This is pretty simple. This doesn't give an idea of the real use of keras. also there is no programming assignments.
교육 기관: Eslam G•
Jul 19, 2019
this course is very useful for beginners
교육 기관: Ostap O•
Jun 27, 2019
It is a great intro but a very limited course. Short videos and a small number of examples, for example, Transfer learning could be more in-depth. Week 4 really made a few obvious changes in the code. I do think it's great material, but all of it could be made into a 2-week course instead. Thanks for your efforts.
교육 기관: Heman K•
May 04, 2019
I enjoyed doing this course on CNN in Tensorflow. Thanks for the lectures by Laurence Moroney. And it is always a pleasure to hear Andrew Ng explain even difficult concepts in simple terms. He is one of my favorite teachers online, and reading about his ML course in a New York Times article back in 2012 or 2013 made me completely change my career direction and motivated me to eventually get into cloud and Big Data! And thanks also for the exercises on codelab. That makes it really convenient to learn and experiment with Machine Learning and Deep Learning.
I did take the first course in the Deep Learning Specialization early last year, but didn't get a chance to do this until now. Looking forward to completing the remaining three courses sometime this year.
교육 기관: James V•
Aug 28, 2019
I finally feel confident that I understand the basics of Convolutional neural nets and what function the various layers serve. It took a Polymath computer engineer/science fiction writer to finally break that mental block and get through to me. Take this class you won't regret it.
교육 기관: Adhikari M T B A•
Jun 16, 2019
Well balanced short and sweet course with practical programming exercises as well as solid theoretical background superbly presented by outstanding tech experts. Looking forward eager for next courses of this series. Thank you very much!
교육 기관: George J C•
Aug 23, 2019
Very informative and the lessons are extremely very well distilled! I came into this course feeling I understood Convolutional Networks and feel as though taking this course and complimentary quizzes provided value to my knowledge base.
교육 기관: Mo R•
May 27, 2019
It's an amazing course, the video lectures are fruitful and the contents of the courses are well designed, the instructor is talented and his explanations are extremely helpful, it's one of the best courses taught on Tensorflow!
교육 기관: Charlie M•
May 01, 2019
A patient and coherent introduction. At the end, you have good working code you can use elsewhere. Remarkably, the primary lecturer, Laurence Moroney, responds fairly quickly to posts in the forum.
교육 기관: Subhadeep D•
May 20, 2019
Very brief and precisely taught implementing various techniques in Convolution Neural Networks by using Tensorflow. Quite time saving and a good one to boost your skills.
교육 기관: Ivelin I•
May 05, 2019
Many thanks to Andrew Ng and team for the great balance of theoretical background, practical references and hands-on programming exercises.
교육 기관: behnoud•
Aug 20, 2019
thanks,,,thanks,,,thanks,,,this is the biggeset revolution in tensorflow,,,thanks Laurence
,,,thanks andrew because of this course
교육 기관: Hoang N M T•
May 04, 2019
It's a perfect course to learn TensorFlow for CNN, and it is extremely easy to understand. Thank you very much!
교육 기관: Antoreep J•
Apr 21, 2019
In the workbook section, the question colab notebook opens up the answer notebook, please rectify the same.
교육 기관: kaushal•
Aug 23, 2019
got hands on , many stuff of cnn , great content. Thank you team
교육 기관: Raffaele G•
May 10, 2019
Great course! I can't wait to going further and deeper. Thanks
교육 기관: Asad A•
Aug 23, 2019
Learnt a lot and believe me this is perfect way to teach.
교육 기관: Egon S•
Apr 24, 2019
Easy to follow and very good explanations
교육 기관: Dmitry S•
May 03, 2019
Consize notebooks. Clear explanations
교육 기관: Oliver M•
Apr 21, 2019
Great Course! Can't wait for part 3!