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Вернуться к Convolutional Neural Networks in TensorFlow

Отзывы учащихся о курсе Convolutional Neural Networks in TensorFlow от партнера

Оценки: 7,650

О курсе

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....

Лучшие рецензии


14 мар. 2020 г.

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..


12 нояб. 2020 г.

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!

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1151–1175 из 1,179 отзывов о курсе Convolutional Neural Networks in TensorFlow

автор: Parth

12 сент. 2019 г.

coding assignment should be included otherwise it is easy to get certificate

автор: mukul k

4 апр. 2020 г.

expecting more advance topics instead of just using Keras.

автор: Lendixful

14 авг. 2021 г.

The jupiter notebook exercises are a mess, pls, fix them

автор: Oliver J

3 нояб. 2020 г.

The last assignment is poorly designed and a real pain.

автор: Hanzhao L

11 февр. 2021 г.

The practices were poorly designed.

автор: Cynthia E

30 мар. 2021 г.

Assignments are not well designed

автор: Gunes D S

12 янв. 2021 г.

Very little content, ridiculously repetitive. Missing info in the last assignment made me waste a lot of time. I wouldn't mind spending time on that assignment if it had been actually challenging. Course designers should consider putting serious time and effort into the preparation of the hands on materials. There is some useful information in this course, but I passed without learning much because of poor design. I still have no idea how to design a good model based on the data set, how many filters to use in each convolution, how many layers in total, how many nodes in the dense layer, etc. The instructor keeps recommending "trial and error", which is fair but I would expect the discussions to be a bit more thoughtful and deeper than that, especially given the price of this "professional certification". This course is falsely advertised as intermediate level, it is actually introductory level, albeit being too simplistic compared to some other great substantial introductory level courses on Coursera.

автор: Alessandro S

3 нояб. 2020 г.

Honestly this course was a bit of a disappointment, didn't really learn anything that can improve how effective i can produce a neural network, on the assignments the hardest parts was coding tasks that was never explained in the course, like reading and copying files, and that has not really anything to do on how to build a neural network, some of the examples provided did not really worked (as the accuracy was poor and always over-fitting), for the last assignment i cheated as using image generator lead to a really poor results so i just skipped and train the model using directly the images.

My suggestion spend more time on what strategy are used to improve the model when the results are poor as the model under-fit or over-fit, otherwise it looks like you add and remove layers until you got lucky.

автор: Fabian A R G

2 июня 2021 г.

I am sorry for the 1 star but is time that deeplearningAI take course content difficulty a bit more precise. I know and I appreciate a lot what you are doing on spreading the knowledge of AI through many varied content, nonetheless if you put that the course is intermediate you should aim to make it intermediate. This is pre-introductory level course and I would have appreciated knowing that so I just skip it an go through a more advanced option. I still finished it as I already paid for it. It is still a well organized and fun course as usual, the problem is that this has absolutely no value in terms of "real world" examples as you put it...

автор: Tal F

13 авг. 2020 г.

What a disaster! I spent more time trying to game the scoring service into accepting a correct answer (and reading in the forum how other frustrated users managed to do it) than actually learning about tensor flow. Such a shame because there were some interesting topics. There is no TA answering questions in the forum either. It doesn't feel like any effort has been made to keep the course current and updated, addressing issues, etc. And the lab work was actually very repetitive - some were almost identical to previous ones.

автор: Brad G

4 апр. 2021 г.

Final lab was a total shit-show. Made you jump through hoops to run off and learn minor things which weren't covered in the course but were highly germaine to passing. Tons of technical problems with getting final lab to submit - reported by many users for over a year - never resolved by Coursera. But for the course itself, it was highly redundant - going into longwinded explanations over several videos of very simple things, often covered in the prior course.

автор: Oliverio J S J

19 окт. 2021 г.

I am very disappointed with this course. The lectures consist of 1-2 minute videos and 30 second lectures. The quizzes seem unserious and the exercises are data organization tasks and not TensorFlow programming, since the TensorFlow related parts can be solved by copying and pasting code snippets they give you in the Labs. Even the exercises in weeks 1 and 2 are the same, just changing a function call! I didn't expect something like this from DeepLearningAI.

автор: Maged A

5 дек. 2020 г.

Course is not properly structured. Transfer learning was using a very special case not the general case.

It is clear that course is just a collection for some scattered old videos and materials. You will realize that at the end of the course when you find that final assignment is NOT relevant at all to the material. Final assignment is a nightmare where there are no guidelines at all. There is no support at all from Coursera. it deserves 0 out of 5 not 1.

автор: Slav K

23 сент. 2019 г.

1) material is boiled down to no-brain

2) questionnaires have incorrect terminology (like method vs parameters)

3) with almost no mandatory assignment the value of certificate is dubious (see point #1)

4) Please stop marketing this course as about TensorFlow. it is all about Google's implementation of Keras and Keras only.

5) The code in course DOES NOT WORK with TF 2.0-rc. Thus student with 2.0 can't submit assignments.

автор: Joseph A

11 дек. 2020 г.

The course overall was great, but several notebooks were really frustrating, *especially* the final notebook in the course! There are literally 0 text cells that explain what is happening, 0 information on the goal, 0 information on the data we are working with, is it dogs or human or hand pictures? Are there 2, 3, 100 classes? Literally 0 information. This notebook was super frustrating to complete.

автор: Aladdin P

4 авг. 2020 г.

On the first course I gave more detailed feedback why I disliked the course, and unfortunately those ideas and feeling are even stronger with this one. Summary: The course is way too shallow and puts focus on many different things rather than what it should have done which is build on the deep learning specialization and do in depth focus on tensorflow.

автор: Jeremy L

9 апр. 2021 г.

This course severely lacks depth, and the explanations are almost non-existing. Some theoretical background is completely missing and I wonder what the target audience is? Beginners will not be able to follow as many things are left unspoken and intermediate to expert learners will be left with a feeling of incompleteness. Big disappointment.

автор: Phillip B

6 мая 2021 г.

The discussion boards are unmoderated and none of the instructors are active. You need to go outside the scope of the program to get your code to work. Also their grading software often crashes because of THEIR code. I do not think they tested the class prior to uploading the materials.

автор: Jesús A M V

28 июня 2021 г.

It feels definitely rushed out and half-assed. The assignments are a joke. If you don't come with a prior understanding of the material being taught, you're in for a hard time. Then again, if you have to know what the course is trying to teach you, then the whole thing is pointless...

автор: Marco F d S

3 дек. 2020 г.

Last grade is the hell, the loading cvs file with the default Lab code, doesn't work, we need to use a solution found by another student, lot of people complaint, but cours not updated... Please fix this, we lose a lot o time to grade the last Exam, of week 4 :(

автор: Michael C L

6 апр. 2021 г.

The last assignment is severely broken and provides no reasonable instructions. When taking the final test you must dedicate 2-3 extra hours to sifting through user posted discussions to succeed.

автор: Jakob A

29 нояб. 2021 г.

Notebooks don't match lessons. where the fuck did week 4 assignment come from? It has nothing to do with multi-class classification and uses several techinques never covered.

автор: Samiul B

23 июня 2020 г.

Very less lecture videos, most are reading based. By reading, it is hard to understand the topic and code implementatio.

автор: Matthew F

28 мар. 2021 г.

Poorly constructed labs in this one, made it take much longer than needed to understand the course content.

автор: Anders S P

11 янв. 2021 г.

Spent 10 times as much time making the flakey grader code happy than actually learning the subject