12 de nov de 2020
A really good course that builds up the knowledge over the concepts covered in Course 1. All the ideas are applicable in real world scenario and this is what makes the course that much more valuable!
11 de set de 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.
por Edgar C O•
20 de jul de 2020
As a follow up of the course "Introduction to TensorFlow for Artificial Intelligence, Machine Learning, and Deep Learning" and as an introduction of the convolutional neural networks for the case of image classification, again, the course is great. The content and the exercises in this course are more challenging and more entertaining to design/program.
por Himansh M•
10 de dez de 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
por Sakshi A•
4 de mar de 2020
I have certainly enjoyed taking this course. The instructor has been so good at keeping us interested in the course. It didn't really felt like learning. I have learned so many awesome things in this course to help me with the current job as well as inspired me to do some fun work on the photos I have taken myself. Thank you for this course. :-)
por Eulier A G M•
17 de jul de 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.
por Wei X•
24 de set de 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.
por Victor A N P•
25 de ago de 2020
Very good course and a good sequel to the first course. These courses give what we need to try our own projects. The course doesn't teach much theory, but it makes us interested and make us search and try to learn on our owns. The notebooks provided in this course, however, aren't as good as the notebooks provided in the first course.
por Pablo S•
12 de jun de 2020
Muy instructivo y activo. A uno como estudiante lo obliga a interiorizarse de verdad en los conceptos para comprender mejor las etapas que se deben implementar para el tratamiento e implementacion de una red neuronal convolucional. En general, con explicaciones claras y comprensibles puedo decir que este este un curso muy bueno.
por Anil K S•
12 de jun de 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 .
por Sagar P•
24 de ago de 2020
Precise and to the mark. Good brief up of the concepts. 5 stars for ease of implementation through programming assignments. Suggestion to fellow learners: Couple these courses with those by Andrew Ng, so it would be the best merger of theory + implementation. Laurence Moroney never fails individual's expectations. :)
por Mateus d A D P•
19 de out de 2020
This course presents a more in-depth look at CNNs in comparison to the first one of this specialization. Subjects as Image Augmentation, Data Generators and others are taught about. The only thing I didn't find quite right is the final assignment. I could be wrong here, but it seems it wasn't designed properly.
por Ara B•
19 de ago de 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.
por ALVARO M A N•
9 de dez de 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!
por Deepak V•
2 de mai de 2020
This course builds on the previous introductory course in the Specialisation. Not only do the four exercises provide practice towards neural network implementation, they also provide a chance to use Python for organisation and manipulation of data, pre-learning.
A fantastic and concise course over all.
por Aditya W•
22 de jan de 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.
por Jian C•
14 de mai de 2020
This course is a very good introduction to Tensorflow and CNN. I have taken Machine Learning theories at school and this is a very nice **programatic** supplement to my course. I think this would be even more helpful if I took it before I learn the theories. I would have been in less trouble then.
por Karan S•
11 de abr de 2020
It's amazing how far we've come in image processing. I remember using basic filters like sobel edge detector during my undergrad. And now we are here, being able to get SOTA results in just few minutes. I wonder how those Phds who were working on handcrafting filters ~2010 would have felt.
por Anujeet S•
14 de dez de 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.
por Sanjay M•
13 de ago de 2019
Very well thought through course for Convolution Neural Networks using Tensorflow, covering some of advances topics like transfer learning, callback and review convolution layers. I already had understanding about CNN and these topics. This course shared scenarios when it is used.
por Thuyen T D•
27 de ago de 2020
The course was amazing, but the thing i don't get it is the 'sparse_categorical_crossentropy' must be use in the last exercise notebook. In the video(s) ,Laurence introduced only 'categorical_crossentropy', hope somebody could upgrade the notebook to suitable the lessons. Tks.
por Ozgur P•
2 de mai de 2020
Really good course, but recommend doing deeplerning specialization first before doing this one or doing them together. Because Andrew Ng explains really well how convolutions work, and without this background info, it will be difficult to understand the concepts in this course.
por Syed A A•
25 de ago de 2020
Really impressed by the work of the team. It is designed specially for the beginner to advance their career and be expert the emerging AI field. With the help of high quality videos and project based assignment one become expert hoe to deal and tackle real world problems.
por Zahid A•
4 de ago de 2021
What an amazing set of courses. Full practical and to point. No time wastage. Believe me if are interested in any course and DeepLearning.ai has it then blindly just enrolled in it as they have the best courses in the coursera platform. Thank you Laurence and Andrew Ng.
por samina y•
27 de mar de 2022
It was easy to follow up all the lesson because of the way the course has been structured. I even tried in other places to learn tensorflow but i was not able to continue after few days. but this structured course was the best. I am confident about the knowledge i got.
por Simon Z•
10 de set de 2019
Excellent. I learned after a couple of years working with neural networks new topics and implementations. I think it would be a good idea to include also here an exercise that gets graded at the end such that we take our time and can try out if we can make things work.
por Abhinav S T•
22 de jun de 2019
The week 1 is a bit casual but where as the remaining one's are just awesome learnt a lot like how to implement a model without overfiting and learnt how to implement transfer learning and multi-class classification problem, really worthy taking up this course....!!!