Mar 09, 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?
Aug 14, 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.
創建者 Antariksh P•
Jul 10, 2019
Great course but should go in-depth about the functions used. Also, the part about making a custom classifier for multiple categories (more than two categories was missing)!
創建者 Juan F P•
Jul 14, 2019
The course was great, and it was a wonderful introduction to Tensorflow, I would like to go beyond the basic, having more technical material that cover the topic more deeply.
Jul 15, 2019
Good introductory course.
創建者 Kristopher J•
Sep 01, 2019
The course has a lot of good material, and is a great follow-up to the more theoretical Deep Learning Specialization.
However, I can't give it five stars because the exercises are a bit repetitive, and the quizzes have some very poorly worded questions. I know this is a new course, so I hope they can smooth out some of these rough edges.
創建者 gu t•
Aug 30, 2019
too easy for experienced programmer, only introduce keras instead of full tensorflow api, it will helps if an advanced course can be offered.
創建者 zhou s•
Sep 01, 2019
Elementary introduction to Tensorflow
創建者 Mr. J•
Sep 06, 2019
significant advancement from previous courses
創建者 Daniel P G•
Sep 05, 2019
Very beginner friendly. Evaluation task could be a little more challenging than just copy-pasting the example code.
創建者 Avinash M•
Sep 06, 2019
I thoroughly enjoyed the course and programming various CNNs on TensorFlow. However, in certain lectures (especially the ones with the horse/human data sets), the instructor could spend some more time explaining the process of downloading and storing the training and validation images. It took me some effort and quite a lot of Googling to figure out those parts of the code. While that might not be directly related to the task at hand (binary classification) it is, in my opinion, necessary to understand some of these ancillary tasks as well. Perhaps these explanations could be included as optional videos for those who wish to understand these features of TF.
創建者 Michalis F•
Sep 06, 2019
too introductory, can be done in a couple of hours, very good instructor
創建者 Nikolay R•
Sep 11, 2019
Very, very basic course for absolute beginners. It makes sure you know enough to build and train models for simple image recognition tasks. 4 weeks is a crazy long period for it, though. I finished it in 2.5 days (I have previous exposure though), but even a beginner should be able to do it in 1 week.
創建者 Richard H•
Sep 13, 2019
Great introduction to using Tensorflow to implement convolutional networks.
I took the Stanford course by Andrew Ng first, so many of the concepts were very familiar - in some cases, the detail was just a little bit shallow - probably to avoid interfering with getting on with implementation - but this course certainly had references outside the course to some more detailed information on topics like how convolutions help identify features or the learning factor.
The jupiter notebooks were great in that you don't need to worry about the environment much - it's already set up - a big worry for me for many of these types of courses. But there were quirks, and a few times I (and some of the other students) could get tripped up for a little while. If you are a developer like I used to be, then troubleshooting and debugging environment/code issues is a small hurdle though.
Kudos to the instructors and those that set up the course - this is otherwise very hard material to teach and set up good "hands on" evaluation, which they did really well, a couple kinks aside.
創建者 Xinhui H•
Sep 15, 2019
Good introductory course. With a lot of focus on codes. Lack of theoretical stuff though.
創建者 João A J d S•
Apr 30, 2019
It's a great course! Very well structured, with an amazing amount of jupyter Notebooks (Colab) to work with, in a real hands on approach.
Just one criticism, which is why I didn't classify it as 5 Star: There isn't much of an evaluation. The tests are a bit easy, and it would be good to have at least one extensive assignment (maybe with other datasets...).
It's just that I feel the contents were really good. But if I can just pass the tests easily, I feel it doesn't really count as much of a "quality stamp" (to have passed this course).
創建者 James L•
Jun 12, 2019
創建者 Abhijeet M•
May 26, 2019
helpful insights about convolution and pooling. I could see how they work together.
創建者 Abhijit V•
Sep 20, 2019
Got some basic idea of deep learning and tensorflow
創建者 Mohamed S R I•
Sep 22, 2019
Laurence is an expert in this field. The material covered in this course is relatively basic, but I think it is a good introductory course for TensorFlow. I was expecting more / elaborate material for the graded assignments, though.
創建者 Manuel A•
Sep 21, 2019
Basic tensorflow code and simple examples, its ok to getting started
Sep 21, 2019
after Dr. Andrew Ng's introduction courses, this one provides good chance to play skills with tensorflow.
創建者 Gerardo S•
Sep 24, 2019
excercises could be better
創建者 Jim D•
Sep 25, 2019
I really liked that it was very hands-on and made it very quick and easy to get up to speed on using TensorFlow for Machine Learning. That said, there was a lot less content that I expected (I finished the '4-week' course in about 1.5 days), and I was a bit disappointed that the focus was exclusively on image classification. A little variety in terms of the problems being solved would've been nice.
創建者 Jefferson R•
Sep 27, 2019
Sep 29, 2019
Good intro to Neural Networks, but would recommend going through other Machine Learning courses if a complete beginner.
Oct 01, 2019
This is a great course with very useful lessons that helps the students feel confident about implementing Deep Learning solutions. It is a perfect follow up for Deep Learning Specialization which lays down the theoretical foundations. The instructor is great, and he talks about real world problems (not just Fashon MNIST but non centered, colored and large images) and explains them very clearly.
There is some amount of lack of attention to details in the course which manifest itself specially in the code (typos, code and code comments not agreeing with each other, and entire lessons which are slotted for 10 minutes or more but dont have any action other than pressing the "mark as complete" button, which makes you feel that you are missing something. Also the discussion board isnt as responsive (especially moderators) as the other Deeplearning.ai courses have been in the past.