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Voltar para Convolutional Neural Networks in TensorFlow

Comentários e feedback de alunos de Convolutional Neural Networks in TensorFlow da instituição

4,315 classificações
656 avaliações

Sobre o curso

If you are a software developer who wants to build scalable AI-powered algorithms, you need to understand how to use the tools to build them. This course is part of the upcoming Machine Learning in Tensorflow Specialization and will teach you best practices for using TensorFlow, a popular open-source framework for machine learning. In Course 2 of the TensorFlow Specialization, you will learn advanced techniques to improve the computer vision model you built in Course 1. You will explore how to work with real-world images in different shapes and sizes, visualize the journey of an image through convolutions to understand how a computer “sees” information, plot loss and accuracy, and explore strategies to prevent overfitting, including augmentation and dropout. Finally, Course 2 will introduce you to transfer learning and how learned features can be extracted from models. The Machine Learning course and Deep Learning Specialization from Andrew Ng teach the most important and foundational principles of Machine Learning and Deep Learning. This new TensorFlow Specialization teaches you how to use TensorFlow to implement those principles so that you can start building and applying scalable models to real-world problems. To develop a deeper understanding of how neural networks work, we recommend that you take the Deep Learning Specialization....

Melhores avaliações


Sep 12, 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.


Mar 15, 2020

Nice experience taking this course. Precise and to the point introduction of topics and a really nice head start into practical aspects of Computer Vision and using the amazing tensorflow framework..

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26 — 50 de 655 Avaliações para o Convolutional Neural Networks in TensorFlow

por Dora M B

Aug 27, 2019

It's a great course. I enjoyed it!

por Chintada A

Aug 21, 2019

really nice introduction to CNNs

por Zeev S

May 14, 2019

Clear, concise, well designed


Aug 26, 2019


por Edir G

May 11, 2019

It's great to learn about data augmentation techniques and how to implement this. This is a great complement for the's course on Convolutional Neural Networks.

por Vedang W

Apr 18, 2020

The course has some great parts such as augmentation and transfer learning, but my expectations were understanding Tensorflow at a deeper level.

por Kaustubh D

Aug 06, 2019

This course is taught excellently, but there is very little content at least from a programming point of view. There was no need of an extra week for only specifying the differences of binary and multi-class classification in code. Rather, there could have been more covered if codes of different output structure like object recognition where the output is not a flat map could be covered. If it has been purposely done to keep the course open to even newbies in Machine Learning, then there should have been a course focussed for those who have done Andrew Ng's ML/DL specialization.

por Deepak A S

Apr 17, 2020

This course doesn't talk about tensor flow. But uses keras only. The title is misleading!

por Md. M R

May 21, 2020

Good, but not so good. they could have introduced tensorflow 2.0s functional api

por Paweł D

May 15, 2019

Pretty basic level, aimed rather to beginners.

por Dan G

Apr 22, 2020

This course is extremely disappointing. The content is very shallow, you'll get more from just following the keras tutorials in the official tensorflow docs. Also, since this specialisation only seems to cover the keras api, perhaps the title is a bit misleading.

On the plus side - it is pretty easy to complete the whole thing in a day and very easy to knock it out before the free trial ends. But honestly, even for free, I don't think it is worthwhile.

The material is very presented in small repetitive chunks, where you'l basically just be running the same notebooks over and over with one small new function thrown each each "week". The quizzes and assignments are riddled with typos which I think is a poor show for a paid for course.

The assignments are basically just copies of the coursework notebooks. No thinking required.

I really would not recommend this specialisation. Your time will be better spent elsewhere. It is such a pity as the previous courses by Andrew Ng have been of such high quality.

por Walter H L P

Aug 06, 2019

This course is so short in content that, in the whole last week, it is explained a trivial concept about multi-class classification. Besides, the last quiz recycle questions from the previous quizzes from this and the previous course. It is clear that the course was made in a hurry once the notebook examples lack in written content or figures explaining the subject. Finally, there is no practical assignments in this "Tensorflow in practice" course.

por Jobandeep S

Apr 21, 2020

the exercises are not very challenging and most of them are the same as the practice colab notebooks, there should be more variety. And also the grading in the exercises is not good there are a lot of errors and it should be made more robust to individual changes made by the student

por Roberto E M C

May 01, 2020

Very shallow and full of typos! And the staff doesn't care.

por Pedro A F F

Feb 08, 2020

It is ridiculous.

por Juan-Pablo P

Feb 20, 2020

This was a great course to go more in depth about the use and implementation of convolutional neural networks. Learn the concept and implementation of "transfer learning" or "inception" to take advantage of CNN trained over a much larger dataset and fine tune the DNN to specialize on a different (but smaller) problem. It was great the learn that one can drop out some neurons from the pre-trained CNN in order to avoid overfitting and specialization. Changing from binary classification problems to multi-class problem is very easy to implement in Tensor Flow / Keras.

por Muhammad U

Apr 14, 2020

Excellent course for a beginner like me. It definitely helped me gaining the concepts and insights of transfer learning and the multiclass classifiers. I am confident now in dealing with the convolution neural networks, coding them from the scratch and to achieve the desired accuracy. The concept of dropout layers has been conveyed in the best possible manner and its affect on the validation accuracy can be easily observed. I would like to appreciate the efforts of the team of Coursera and the instructors for laying down an extraordinary online lecture series.

por Scott C

Jul 10, 2019

Great for people who want to not delve too deep into theory and learn the latest tools to get going quickly. I had already done the Deep Learning specialization so I recommend that as a great complement for the theory part. I learned everything I needed to get going with a practical application in this course. My only complaint is that I felt that the quizzes were poorly designed - most questions emphasized whether you remembered a specific API's argument name, or some questions were a bit ambiguous. Otherwise, highly highly recommend the course.

por Ben R

Dec 28, 2019

This was just an exceptionally well-done course. It's not complicated, but I don't think the point of it is to be complicated, just practical. All in all, I enjoy the teacher's style. If you're trying to understand the fundamentals of the theory and mathematics, these courses aren't for you; if you're looking to just gain a practical and useful working knowledge, then this is a great starting place. I took it to just round out my understanding of Tensorflow via Keras; this was a great course for that.

por Hannan S

Oct 28, 2019

First of all, the course was amazing! I found it great for the following reasons:

- Laurence Moroney (Instructor) was very professional and clear while delivering the knowledge

- The introductions by Andrew NG were really nice

- Easy to understand codes and understanding of thr underlying principles

- Varied topics such as CNN, NLP & Time Series

- Very insightful by providing expert opinions about different ways of model optimization

I really enjoyed the course and I thank the instructor for the same :)

por Victor H

Oct 31, 2019

I am already familiar with machine learing and convolutional neural networks, and before starting using the TensorFlow framework I wanted to develop my own know-how in order to really have control and knowledge on what am I doing. Now that my C++/CUDA implementations work, I feel allowed to use a better tool like TensorFlow / Keras, and I am really discovering their power and flexibility, and I am getting really excited of the productivity that I can gain in my projects thanks to them!

por neil h

Jul 30, 2019

Laurence Moroney presents another superb primer on the mechanics of tensor flow. Heavy on image analysis, we see how convolutional nets — concatenating stages of convolutional filters and pooling — extract features from images at whatever scale they appear. The exercises contain a modicum of basic-python skills reinforcement. Upon completion, one is equipped to tackle other common problems, e.g., the usps handwritten-digits challenge

por Mastaneh T A

Jun 03, 2019

The pace of these two courses and the extremely to-the-point nature of the explanations, examples, and exercises enabled me to implement customized CNN-based codes my own data in only 5 weeks. Now I am definitely more confident to explore and implement more complex models and concepts in Tensorflow. Thanks to Andrew, Laurence, and the rest of the team for the very efficient learning experience and for sharing their knowledge and expertise.

por Rudraksh J

Apr 04, 2020

Great course, great content, and the best part is you are getting quiz and those "Challenging, interesting, excellently" designed assignments which surely test and improve your real skills. I'm just excited about those assignments every time I progress with a week.

Till now I have completed the first two courses of this Specialization and I'm sure the rest would also be great. I would be taking them all!

por gjycoursera

Jul 01, 2020

greate introduction to Image Classification. The skills is very very useful!

I like this course.

My advise to other learners is reading keras official developer guide( when you learn this course. That will be very useful.

Besides, I want to get more skills about Image Segmentaton, Object Detection ,etc. So I hope Deeplearning,ai launch more advanced Computer Vision courses.