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 Ronny K O•
A while back I chose to do Java over Python because I thought it was easier. Looking back now, I realise that it is the other way around. I have learned about Tensor flow and Convolution Neural Networks and as it turns out, Python is 10 times easier than Java. I am glad I tried out this course.
Thanks a lot Coursera
por Jonathan P•
I liked the course very much!
It is definitely required to know python quite well and would be good if one had a liitle bit of pre-knowledge in the field of ML / Stat or equivalent.
Everything was very well explained, the exercises had exactly the right amound of complexity and I never felt "lost" during the course.
por Pratik M•
The tutor Laurence Moroney is very good in explaining Neural networks basis with Tensorflow. I highly recommend this course to any individual planning to become ML Engineer. I would still look up for indepth study on some topics like knowledge on when to use different number of ConvNet filters (eg. 16, 32, 64 etc)
por Shilin G•
I think this course is great, serves its purpose of introducing TensorFlow as a tool. For people who are looking for more in-depth knowledge of deep learning, you should go for a proper deep learning specialisation. This one is great for people who already know something about deep learning but new to TensorFlow.
por Melwin J•
it gave a very good introduction to tensorflow . i realy like the course. I had spent a lot of time learning algorithms, working and the theory behind artificial intelligence .this course has helped me to put all what i have learned to practical use. i suggest this to all those who want to atart with tensorflow.
Very crisp and clear understanding of Tensorflow in AI , Deep learning.
Post this course I am well versed with programming paradigm of Basic NN, Convolutions, MaxPooling, Filers , CallBacks , model training,validation, prediction. Appreciate the exercises and explanations. Feeling handful of experience with it.
por Artem D•
That was interesting and not hard, so you won't be afraid of coding =). I do not recommend to take this course if you have no theory base regarding NNs (in this case first complete DL specialization by deeplearning.ai). This course is high-level, expecting more of deep dive in the following courses =). Peace!
por Jian C•
Solved a lot of my problems that come up to me when I read the code written by other people in Github/Kaggle. I have taken ML course with python. (no framework) This would be a great material for someone like me who know some ML and don’t know Tensor-flow. You can go over the whole course in just 1-2 days.
por meet d•
This course provides knowledge about Tensorflow APIs, not the fundamentals of Deep Learning. So, I highly recommend learners to complete Deep Learning Specialization course offered by Deeplearning.ai first. This course will refresh all the concepts. Course covers all the scopes for what it is developed.
por Mathis V E•
For someone new to AI/ML, this is a good place to start. If you're already familiar with deep neural networks, conv nets, ect (as explained in Andrews Deep Learning specialization) this course will be a breeze, but it will teach you how to use tensorflow as intended. I did this course in about 3-4 hours.
por Ishwar N•
The best practical oriented and hands on course on Tensorflow, highly recommended. Laurence Moroney (Google) is a great teacher, love his pedagogy, he does not delve too much into mathematics and still makes concepts very clear, because of this I could finish the course in 3 evenings instead of 4 weeks.
por Rodolfo V d A•
I loved this course! Thanks to Professsor Moroney for his excelente lectures.
(If a could contribuit with some thing, maybe more exercises and few more explanations about the parameters on function. Of course, wether the explanation on parameters come in futures course, please desconsider my comment. )
por Omar R L•
Great course, I was really interesting. Just one thing the notebooks are not well explained like we're used in the deeplearning.ai with Andrew. But no problem it makes it more challenging. Another thing, I don't know if this course is using the new version of tensorflow but I hope it's using it (2.0).
por P.sai c•
as a beginner i have no idea on how to implement the CNN even though i know the concepts of CNN it was hard to implement but this "Introduction to TensorFlow for Artificial Intelligence, Machine Learning, and Deep Learning" gave me a basic idea on how to implement them and the tutorial was too good
por Arun J•
A course well designed for those who prefer a hands-on approach to learning and development in the AI-ML space. Thank you Laurence, Andrew and the Coursera Team for helping me understand the basics of Neural Networks, TensorFlow and the practical applications of the technology through this course.
por Masih B•
Although this course is titled as Introduction to TensorFlow, It has tought me how to apply my theoretical knowledge on deeplearning using Tensorflow. I must certainly advise people how have learned or study deeplearning to pass this course, As it would teach you exciting materials on this topic.
por Ajay C•
It was short and crisp, if assignments were bit more challenging it would have been a great learning. All things to the point no hour long videos to bore us. It is recommended for beginners. For mid to expert level u can complete the whole course in 4 hours with all the reading and assignment.
por Dr. S P•
This course is well structured with very good instructional delivery. The vivid explanations and the discussion forum does not let you feel that you are alone. There are answers to almost all our doubts even before we post them in the forum. Looking forward for the next course in this series.
por Gulshan R•
This course was really beneficial for me. It helped me understand the concepts in more depth. The mentor helped a lot by creating notebooks of algorithms being explained. This truly helped in visualizing the features or what really is happening behind the training of the model. Thanks a lot.
por Victor A M B•
Muy buen curso, aprenderás como implementar una red neuronal desde lo más básico. Recomiendo comenzar este curso después de ver los primeros cursos de la especialización en Machine Learning de deeplearning.ia, así se comprenderán mejor lo que se está haciendo y será muy trabajable el curso.
por Kimon-Aristotelis V•
I loved the way the modules are structured in this course: First, the instructor explains to you, then you can play with the code after you need to create the code and in the end, they allow you to use the Colab and almost redo the same. By the end of the course, you master the material :)
por Miguel Á L J•
Quise poner mi review en inglés, pero creo que servirá más para aquellos que hablen español. Es un curso simplemente impresionante, soy principiante en usar TensorFlow y es una muy buena manera de introducirnos en este fascinante mundo. Gracias a la UNAM que está financiando estos cursos.
por Subhradeep H•
Extremely recommended course for those who want to learn computer vision. This course gives great knowledge in the field of TensorFlow and also provides basic to intermediate knowledge in deep learning. I am very happy that I had chosen this course as my first course in computer vision.
por William G•
A rather basic course to introduce you to Tensorflow. The exercises are rather difficult due to the lack of information provided. However, the course is informational, and those who have completed the Deep Learning Specialization previously should have no trouble completing this course.
por S S N•
Overall , an amazing course , and possibly a fruitful use of my time.
The course was smaller than expected , but it opened my eyes to a new method of learning - Learning my trying things out - so instead of getting glued to the lecture videos , I spent most of my time trying things out