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.
par Xiaonuo G•
Using https://colab.research.google.com/ is definitely a good choice because it saves the learners a big chunk of time setting up a deeplearning workstation by herself. The course's source code is commented extensively to ease understanding. Although the technical details and specific explanation of the deeplearning algorithms are pretty lightweight, it's more than enough to get one's hands dirty as a beginner course.
par Dina M•
I really enjoyed the line-by-line code explanation and the right balance between theoretical and practical parts. As a beginner, it is easy to get lost in all different types of layers, optimisers, etc, and this course helps understand a general structure of a neural network program. The Python notebooks that we are given are extremely useful for watching how the things work by experimenting with code. Thank you!
par Neel M•
This is an amazing course, and one can feel the hard work they have put into it. I was able to experience so much theory in practice, image augmentation, dropouts, transfer learning. Learning experience? Much better, it was a learning enthrallment! This is one of those courses which make deep learning looks so easy, and approachable. Highly recommended for anybody, and coursera should have more courses like this.
par Rattapon I•
The course contains a lot of resources and intuitive knowledge for deep learning. They also provide good exercises for demonstrating the idea the instructor tries to convey.
However, I think we need more hints or instruction on assignment. Many times, we got grader errors or some other glitches.We willneed to check the discussion forum if there is any one faced the same problem and a solution or not.
par Tamim-Ul-Haq M•
Very interesting start to TensorFlow. This course although doesn't teach the basics of a ML model (which Stanford's ML course and the Deep Learning Specialization already do in great detail) but gets right down to how you can use TensorFlow for classifying what type of problem such as the basic regression problem to an image classifier. This course offers intuitive on how to properly use TensorFlow.
par Ilias L•
Enjoyed the visualization part where we were encouraged to peek at different parts of the neural networks to understand how features were created.
Could be somewhat more thorough on how different amount of layers and architectures affect the quality of features created and the overall performance instead of encouraging people to just play around.
Useful, to the point and easily digestible intro to TF
par Poornima R•
I loved how this course is structured. I'm right now preparing for my interviews and this course had concepts explained in like awesome way that you could use to answer in interviews. The google colab platform was very helpful and tutor Prof.Lawrence was incredible at explaining the codes line by line. On the whole, I would go over this course over and over again to get my concepts at fingertips.
par Daniel M•
If you just make this Introduction to TensorFlow for Artificial Intelligence, Machine Learning, and Deep Learning Course you can manage to make a few simple codes.
This introduction complements very well with Deep Learning Specialization. In case you have done the specialization, this course will give you the first steps so you can start programming and learning for more complex applications.
par Cheng-Tsu Y•
Great course for starting the implementation of classification model on Keras. Although more detail into theoretical part should be found from other courses or materials, this course definitely provides the very first step in the coding part. For me, with little prior knowledge in python, I did learn a lot by studying the Notebook sample code carefully. So I will recommend this course!
par Timothy Q•
If you're looking for a more theoretical approach, go take Andrew Ng's Deep Learning Specialization first. This course is more of a crash course based from what Andrew has already discussed, and is heavily focused on hands-on application using Python. The course will encourage you to experiment and understand the impact of different parameters in your model. It's fun and challenging.
par Shubhangi S•
The learning process is very explanatory and very easy to understand. the course has many quizzes and programmable problems which allows the learner to get a clear view of how to work with TensorFlow. the course also provides various notebooks where you can experiment by changing the values of variables and see the effect of it in the output which in turn makes the learning valuable.
par Abdulaziz A J•
I am planning on taking TensorFlow certificate, so I finished this course in 5 days. Glad I did that as I did lean how deep neural nets and convolutional neural nets work! I am still in the beginning of my path, so I will keep working hard to finish all of the other courses in order to achieve TensorFlow certificate. Thank you, Laurance and Andrew, for the amazing beneficial course!
par Erling J•
Elegant and efficient introduction to the plug-and-play Google Colaboration application that let's you easily write and execute Python code in the cloud, as well as the Keras API that let's you access the Tensorflow package to use with convolution and pooling layers. The exercises were brilliant as well and I have high expectations about the following courses in the specialization.
par Κώστας Π•
A quiet interesting course that introduce you to TensorFlow, and gives a basic understanting of image processing in Python. The course was well organized with explanatory videos, code scripts in google collabs, and necessary assignments to practise your code skills. Overall I am very pleased that I attended this course, and I am planning to attend more like this in the near future
par Christian D M•
Concise and cohesive course, and was very easy to follow! It was nice to see both the theoretical and practical concepts explained in a manner that a beginner such as myself can understand. They provide many other resources in case I get stuck or need further explanation as well. Thank you for a great introductory course, and I am excited to learn more in the future courses.
par Sohail Z•
Great intro by Laurence, very comprehensible. But i think a bit more work should have been done on presentations for deep learning newbies for them to be able to grasp the concepts of difficult topics like convolutions.
Though i would recommend anyone to first complete Andrew Ng's deep learning.ai specialization first, then start this course, it would be really beneficial.
I think this is a great introduction to Tensorflow 2.0 as a whole. What other reviews may say is that they didn't go into much of the theoretical aspects, yeah that's fine after all this is a course that is meant to be practical by all means. For people who've already taken Andrew's Deep Learning Course for example.
I think the instructor has done a great job! 5 stars!
par Abhishek D•
Liked the course as it did not spoon feed you the answers and you had to go back and watch the videos again to attempt the programming assignments. Overall it was fun learning tensorflow. I am very excited for the next course in the specialization. I would encourage people to do the entire specialization because this course alone wont teach you much about tensorflow
par vaibhav t•
This course is helpful to understand how to create basic deep learning networks and models using library TensorFlow. I understood the implementation of deep learning models using developed python library. But you should have basic knowledge of deep learning before starting the course otherwise you won't be able to understand fundamental concepts used in this course
par Hein A•
Quick, Informative, Intuitive and Interactive is a few of the nice things you can say about this course. As someone with background in theoretical AI but not a lot of practical practices, this was such a useful study. I recommend all you academics with MScs and Bscs to finish this course. Of course it always help to brush up your Python skills prior to the course.
par Jayashree G•
It was a great experience, learning the foundations of neural network. Now I have a clear vision, how artificial intelligence works. All thanks to Lawrence Moroney and Andrew NG, with all their experience and expertise they have in their field, they explained each and every instance where a person could go wrong. Great course I would definitely recommend everyone.
I am a programmer with a little knowledge of statistics. Other courses really dive into the theory and I get lost pretty fast.
This one however just teach you how to use the existing AI libraries without digging deep into how they work and what algorithms they employ.
It was pretty easy for me to follow through with this course and I'd recommend it for any beginner
par Dustin Z•
Fun introduction to tensorflow. This course is best if you completed the deep learning specialization before it this course doesn't go into the details of how everything is working under the hood.
The structure of the course is well done with plenty of opportunities to practice.
There are still a few rough edges to smooth out, but all around really great.
par Joydeep G•
I have completed more than 80+ MOOC from various platforms and many reputed universities and I must say, Laurence is one of the best teacher(s) I came across. The way he teaches (which includes topic content, explanations, and converting complex concepts into simple one) is simply unparalleled.
A BIG THANKS to him and everyone associated with the course.
par Abhinandan M•
A very good start for tensorflow beginners and a concise refresher for those who have already used the tensorflow framework. Loved the way each code was explained but particularly found the part where we can play around with what each filter is learning as particularly important for anyone going forward with this course. Thanks for this great material.