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?
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.
por Ruxue P•
I've been an machine learning engineer for 2 years, taking this course to push myself to learn new TF2 features. I don't think there's focus on the new distributed training feature in TF2, codes are still TF1.x.
I think the last quiz had some really unclear questions, could be improved.
Other than that, I love the hands-on practice part. Wish we explain more on why model performance is so brittle in the horse vs human classification example.
por Amit K•
Although course content seems to be nice but a regular update with the current tensorflow version needs to be done. Also, In course content there are topics listed just to tell that in next section what you will study(even provided 10 mins for that) and that is a complete waste and poorly put in the content section-this needs to be fixed.
On a positive node, this course is very useful to start and I recommended this to beginners.
por Rajesh R•
Great review of TF and the newer tf.keras API in addition to practical advice on deep learning projects. Lawerence has been a pretty good instructor, clear and to the point, with some good exercises. For beginners, though the course skims over some of the basics - although these are covered in Andrew Ng's Deep Learning specialization, which I took some years ago. All in all, a handy course to get cracking on TF and Keras again!
por Ronet S•
Brilliant Course for getting started with Tensorflow. The only thing I would like the instructor to include are explanation for non -TF stuff, like matplotlib codes. It would really help develop additional skills apart from making TF models. Going online to find the working of each command in a different library like matplotlib really broke my flow and my focus . So, that would be a welcome addition!
por Jim D•
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.
por Venkatesan A S•
The course is targeted for an audience with a basic knowledge of the machine learning techniques. With that in mind, it delivers a comprehensive first look at the calibre of the TensorFlow framework. For the more advanced practitioners the programming exercises and the quiz might seem a bit on the easier side. Overall it is a great place to start for those who wish to begin with TensorFlow. Kudos!
por Miguel L•
The contents and instructor is excellent. Unfortunately one is faced with mainly two downfalls. Fist, there always seems to be some sort of submission problem which usually involves some kind of "hacking" from the user's part to make it work. Secondly, it's very hard to get answers to most doubts since the activity in the discussion Forums is very little, specially from instructor-level sources.
por Elias B•
Overall a very good course (with knowledge from the deep learning specialization) to get a deeper knowledge in tensorflow. But sometimes in the exercises you feel a little left alone, because of missing information (example Week 4, which folder should you use, what's the resolution of the images, you can find out but that requiered (for me I had to downloaded the files and check what i needed).
por Andrei N•
The course is quite light even for introductory one. At the same time, I enjoyed examples of NN implementations in colab and elaboration on how the code works. The most interesting for me personaly were hints and techics helping to develop a better understending on how the NN are builing its knowlarge on input data. I look forward to checking other courses of specialization out.
por Harshit J•
That course was superb, but there were much references to other content, ik that was important but just as a suggestion I would say you can put this specialization in 5 courses or add 1 Week in each but please teach that all, by the way 4 stars were just to grab your attention as review otherwise I literally loved the content thank you Mr. Laurence and Mr, Andrew
por Vardaan T•
Should probably spend more time on lectures. They're a little too short, and almost exclusively just designed to discuss snippets of code that help you solve the immediate assignment. I realize that this is a hands-on course, but intuition provided could have been much better. If you want to know how that's done, refer to 3Blue1Brown's series on Neural Networks!
por Kishan K•
very structured from the beginning, the time required to complete this course is calculated very carefully so even if you're a beginner with deep learning you'll be complete the course on time. there are a lot of useful resource links as well which reduces the learning effort. i really liked this course and it made me more confident to pursue the specialization.
por Arun P R•
The course topics were well conversed by Lawrence. But I find it difficult to process the programming assignment, not because its difficult for me, I completed what I am supposed to do and got desired output on it but the submission and grading mechanism is a bit faulty and misleading. The Discussion Forums also got not much mentors or fellow students helping
por siddhanta b•
Really nice course for basic Tensorflow, It will be much better if a real world example is explained with every aspect of machine learning. Like data aquisition, sufficiency, labelling, model building, evaluation and deployment. I am not saying to show the steps how to do it, but some pointers will be nice. Final project should at least include everything.
por Umberto S•
A really simple and intuitive approach to Neural Networks in TensorFlow. Smart and simple examples to experiment by yourself how to build image classification with a few lines of code in python. For me was useful to recap what I already studied in DeepLearning.ai courses. This course was pretty good to do some practical exercises and an overall recap.
por Kalana A•
This is way too easy for an intermediate course I believe. But some of the concepts like visualizing the activations of the layers, writing the custome callbacks are really nice. Overall the explanations were really good and the notebooks gives really good insight and playground to play with parameters and learn how these functions (API) work.
por Michael F•
I like Mr Moroney's videos. He is very good in explaining things. Sometimes he goes a bit too fast through the notebooks. It would be very nice if he could dive a bit deeper into the mathematical/theoretical backgrounds. The theoretical sources for reading are good, but I find it sometimes very helpful if somebody is explaining it. Thanks.
por Jack P•
Great intro to getting started with TensorFlow. Highly recommended to do this after getting the basic theory from the deeplearning specialisation (i'mm the kind of person that likes to understand at least at high level what is going on so would say do the deeplearning first. However if you prefer to do the learn after could do it second!)
por Shehryar M K K•
This course focuses on the practical programming aspects of deep learning networks rather than the theory. It is very helpful to get hands-on training with tensor-flow. I would highly advise taking Andrew Ng's Deep Learning course before taking this course as it makes understanding fundamentals of deep learning more meaningful and fun.
por Lukas A•
Very good to start some coding and get hands-on experience. However, they do not go into depth about what the parameters mean and why it makes sense to set them just as they do it in the instructions. It gives you a great experience, but I am not sure if all this is useful when working with real data on real problems with real pitfalls.
por Kristopher J•
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.
por AbdulSamad M Z•
Excellent course to get a grasp on the basics of ML/DL with Computer Vision on TensorFlow. Lecture delivery is super clear and the exercises nicely complement the material and give you the hands-on work you need. Having taken Andrew Ng's Machine Learning course will significantly help as this course is more practical than theoretical.
por Rishabh C•
Good starting point to learn about training and deploying Deep Learning Models using Tensorflow. Some concepts cause a little confusion regarding the import structure of these libraries. Sometimes only import tensorflow is used while sometimes keras is imported as well. But all the code uses tf.keras , so it gets a little confusing.
por Xuanlong Y•
It's good enough for beginners, but I have to say it's still a little bit easy. Maybe teacher can give us more reading materials or show us more interesting projects that we can reach after this Specialization and I think that can be called an introduction. But anyway, I think the course is better than many tutorials on the Internet.
por Arpit G•
Overall the course is very good . It gives a simple introduction to Deep Learning especially ConvNets. I would have loved if some of the concepts like Convolution were explained in more depth using some cool animations. The good thing about this course is that it never appeared to be a burden , rather it was a joyful experience.