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.
Dec 09, 2019
Very clear explanation on the concepts at the higher level and practical application of it is discussed, demonstrated and also the exercises are of the same way. You will just love learning this way
By Dora M B•
Aug 27, 2019
It's a great course. I enjoyed it!
By Chintada A•
Aug 21, 2019
really nice introduction to CNNs
By Zeev S•
May 14, 2019
Clear, concise, well designed
By NITESH N•
Aug 26, 2019
By Edir G•
May 11, 2019
It's great to learn about data augmentation techniques and how to implement this. This is a great complement for the deeplearning.ai's course on Convolutional Neural Networks.
By Kaustubh D•
Aug 06, 2019
This course is taught excellently, but there is very little content at least from a programming point of view. There was no need of an extra week for only specifying the differences of binary and multi-class classification in code. Rather, there could have been more covered if codes of different output structure like object recognition where the output is not a flat map could be covered. If it has been purposely done to keep the course open to even newbies in Machine Learning, then there should have been a course focussed for those who have done Andrew Ng's ML/DL specialization.
By Paweł D•
May 15, 2019
Pretty basic level, aimed rather to beginners.
By Walter H L P•
Aug 06, 2019
This course is so short in content that, in the whole last week, it is explained a trivial concept about multi-class classification. Besides, the last quiz recycle questions from the previous quizzes from this and the previous course. It is clear that the course was made in a hurry once the notebook examples lack in written content or figures explaining the subject. Finally, there is no practical assignments in this "Tensorflow in practice" course.
By Juan-Pablo P•
Feb 20, 2020
This was a great course to go more in depth about the use and implementation of convolutional neural networks. Learn the concept and implementation of "transfer learning" or "inception" to take advantage of CNN trained over a much larger dataset and fine tune the DNN to specialize on a different (but smaller) problem. It was great the learn that one can drop out some neurons from the pre-trained CNN in order to avoid overfitting and specialization. Changing from binary classification problems to multi-class problem is very easy to implement in Tensor Flow / Keras.
By Scott C•
Jul 10, 2019
Great for people who want to not delve too deep into theory and learn the latest tools to get going quickly. I had already done the Deep Learning specialization so I recommend that as a great complement for the theory part. I learned everything I needed to get going with a practical application in this course. My only complaint is that I felt that the quizzes were poorly designed - most questions emphasized whether you remembered a specific API's argument name, or some questions were a bit ambiguous. Otherwise, highly highly recommend the course.
By Ben R•
Dec 28, 2019
This was just an exceptionally well-done course. It's not complicated, but I don't think the point of it is to be complicated, just practical. All in all, I enjoy the teacher's style. If you're trying to understand the fundamentals of the theory and mathematics, these courses aren't for you; if you're looking to just gain a practical and useful working knowledge, then this is a great starting place. I took it to just round out my understanding of Tensorflow via Keras; this was a great course for that.
By Hannan S•
Oct 28, 2019
First of all, the course was amazing! I found it great for the following reasons:
- Laurence Moroney (Instructor) was very professional and clear while delivering the knowledge
- The introductions by Andrew NG were really nice
- Easy to understand codes and understanding of thr underlying principles
- Varied topics such as CNN, NLP & Time Series
- Very insightful by providing expert opinions about different ways of model optimization
I really enjoyed the course and I thank the instructor for the same :)
By Victor H•
Oct 31, 2019
I am already familiar with machine learing and convolutional neural networks, and before starting using the TensorFlow framework I wanted to develop my own know-how in order to really have control and knowledge on what am I doing. Now that my C++/CUDA implementations work, I feel allowed to use a better tool like TensorFlow / Keras, and I am really discovering their power and flexibility, and I am getting really excited of the productivity that I can gain in my projects thanks to them!
By neil h•
Jul 30, 2019
Laurence Moroney presents another superb primer on the mechanics of tensor flow. Heavy on image analysis, we see how convolutional nets — concatenating stages of convolutional filters and pooling — extract features from images at whatever scale they appear. The exercises contain a modicum of basic-python skills reinforcement. Upon completion, one is equipped to tackle other common problems, e.g., the usps handwritten-digits challenge https://www.kaggle.com/bistaumanga/usps-dataset.
By Mastaneh T A•
Jun 03, 2019
The pace of these two courses and the extremely to-the-point nature of the explanations, examples, and exercises enabled me to implement customized CNN-based codes my own data in only 5 weeks. Now I am definitely more confident to explore and implement more complex models and concepts in Tensorflow. Thanks to Andrew, Laurence, and the rest of the team for the very efficient learning experience and for sharing their knowledge and expertise.
By Rishiganesh V•
Jul 20, 2019
It is really an amazing course, My heartfelt thanks to Mr.Laurence Moroney, for his great teaching and Mr. Andrew Ng for giving these great platform. I Really enjoyed the course. I learned it lot of things here. I am going to take all the specialization in these courses. And It is great pleasure to thank Coursera platform for providing me Financial aid to take up these course.
By Khanh N•
Feb 20, 2020
This course gives me an overview in CNN applying into various fascinating Computer Vision problems, which really excite me. The inspiration that I got would definitely push me to working harder in order to have a successful career as a ML engineer. Also, the teaching style of Laurence is one of the highlight for the course as I found it both fun and effective.
By Himansh M•
Dec 10, 2019
This course is a great addition to the deep learning courses by Prof. Andrew Ng. I got to learn the fundamentals of deep learning from Andrew Ng's courses and learned to programme from here. It's a great course to learn Tensorflow and this course also helped me in my final year project. I'm really thankful to Coursera and deeplearning.ai for this course
By Eulier A G M•
Jul 17, 2019
The course is marvelous explain and with clear, concise & straight forward concepts alike the practice project.
Take your time to understand the concepts, so you can move on.
I'll recommend to watch the specialization of Neural Network from Andrew Ng, to deeply understand the "magic" ( linear regression, matrices, derivatives) of Neural Networks.
By Wei X•
Sep 25, 2019
I originally expected to learn more pure TF related stuff. But instead I learned Keras. Data augmentation with Keras is quite easy. Transfer learning is also easy to do if there is Keras model there already. But I do hope to learn a pure TF tutorial that are more common when you download other people's TF model and practice with your own data.
By Anil K S•
Jun 12, 2019
This was the actual dealing with the dataset saved at local memory location rather than predefine dataset where the dealing with label and directory were ignored which learner actually face problems while learning and handling with the datasets stored at local drive. well this course actually helped for my major year project .
By Ara B•
Aug 19, 2019
Easy to follow. a lot of examples. I was expecting at least one assignment for the final! :)
As for the convolution we never talked about DOG+SIFT or other feature extraction techniques. Also I would like to see how we can separate an object of interest from background e.g. using clustering or a video stream.
By Alvaro M A N•
Dec 10, 2019
I love this, because the instructor make the difficult easy. After ending this course, I believe I would enrolled on the other specialization, to gain a better mathematical understanding of convolutional neural networks but I'm pretty happy to learn the practical stuff, this make possible a lot of projects!
By Aditya W•
Jan 22, 2020
I mainly to learn the various constructs to do various things in TensorFlow, and this course is very well constructed for it. It doesn't explain the actual mathematics though, and I don't blame it for that. It is just designed to help people learn the framework. Overall, a very satisfying experience.
Dec 14, 2019
This course in tensorflow specialization is a must recommended. It builds knowledge from beginners to advance very smoothly, You will be able to get a experience of how to begin coding for tensorflow also be able to understand its core layers, And learning from Laurence is always fun.