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.
автор: luis a•
Sep 30, 2019
The course was fine sometimes I feel too easy. I would like to see more of the available options for the layers, such as padding, stride. filter size, mean average, batch normalization, etc...
Sep 27, 2019
Instructors are really good, but in my opinion, this course should contain Object Detection and Object Segmentation topis.
автор: Gerardo S•
Sep 27, 2019
the last exercise needed a big upload, made it imposible (for me) to do. This was a problem not related to the subject, should use data downloadable directly from internet.
Sep 05, 2019
Please transfer the notebook from CoLab to Coursera.
автор: Dr. H H W•
Sep 06, 2019
Great insight for the practical aspect of TensorFlow, add value on top of Andrew's DL courses.
автор: Kailyn W•
Sep 09, 2019
I need more coding practice, not just quizzes.
Oct 02, 2019
A more advanced course would be highly appreciated.
автор: H M A r•
Oct 02, 2019
The course is really nice. But would be better if the convolutional layers were a bit more detailed. It was a bit difficult for me to understand all the parameters e.g: input/output filter size.
автор: Anand H•
Sep 12, 2019
One challenge i have faced is with deploying the trained models. I find very little coverage on that across courses. It's one thing to save a model.h5 or model.pb. It would be nice if you can add a small piece on deployment of these models using TF Serving or something similar. There is some distance between just getting these files outputted and deploying. TF documentation is confusing about some of these things. Would be nice if you can include a module on that.
автор: Vittorio R•
Oct 06, 2019
Good, but expected more, for example object detection.
автор: Damon W•
Oct 08, 2019
Good practical course. A bit heavy on visual images, but very informative.
автор: Marcos V G J•
Sep 25, 2019
Good content, but lacks exercises that forces us to code ourselves to solve the problemas
автор: Donal B•
Oct 18, 2019
Excellent course. Would have liked graded coding assignments like in the first course.
автор: Brian ( B•
Oct 23, 2019
very practical courses on implementation of CNN in tensorflow. Suggest student also take the deeplearning series with this series.
автор: Leon R•
Oct 26, 2019
Loved the course. I would have liked a module on saving your own models and then loading them later. The Inception one is nice, but it comes with some "niceties" that I don't think you have with loading a home grown model.
автор: Lei W•
Oct 30, 2019
will be nice to have non-third party programming exercises that are graded by Coursera
автор: Bingcheng L•
Nov 12, 2019
автор: Phuoc H L•
Nov 14, 2019
More exercises should be available for students to practice and test their skills.
автор: Mohammed F•
Jul 06, 2019
Could have dived more into the details and inner workings of Convolutional layers but overall awesome course.
автор: Luiz C•
Jun 11, 2019
not challenging enough
автор: Renjith B•
Jul 15, 2019
Good content for classification tasks. But didn't cover anything related to object recognition, localisation and semantic segmentation which are the challenging computer vision tasks.
Jul 26, 2019
A bit too basic and shallow in terms of conducting the lecture. You are left doing most of the things on your own as the trainer assumes you know. Like using the jupyter notebook, configuring the tensorfow. Some of the google collab books do not work or took too long to load, the videos are too short no notes provided at all. After finishing the course there is nothing to refer to and its starting all over again. Given the level of machine learning course with Professor Adrew Ng, the standard is very high and you will expect that same level. Nevertheless, the concepts are very useful and the lecture explain very well. There level of material left for students to practice on their own,like assignments, notes. Not to be referred to existing material.
автор: Muthukumarasamy S•
Aug 04, 2019
Overall learning from this course is less compared to the expectations from a 4 week course. I was expecting to learn variety of TensorFlow implementations for CNN like Face recognition, Object detection. But this course only talks about Image classification. It would have been better if you could also discuss more about implementing various architectures in TensorFlow like ResNets, Inception. Also, You talked only about using sequential layers in Keras and concatenation of layers in Keras is not discussed here. I know all these concepts are discussed in Deep Learning specialization. I was only expecting to learn their implementation in TensorFlow from this course.
автор: Joey Y•
Aug 04, 2019
The course seems to be getting more loose than the first course.
автор: Wellington B•
Aug 05, 2019
need to watch Andrew Ng's course on deep learning before watching this one