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Вернуться к Convolutional Neural Networks in TensorFlow

Отзывы учащихся о курсе Convolutional Neural Networks in TensorFlow от партнера deeplearning.ai

4.7
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Оценки: 3,739
Рецензии: 570

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 deeplearning.ai 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 deeplearning.ai 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

JM

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.

RB

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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51–75 из 565 отзывов о курсе Convolutional Neural Networks in TensorFlow

автор: Eulier A G M

Jul 17, 2019

The course is marvelous explain and with clear, concise & straight forward concepts alike the practice project.

Take your time to understand the concepts, so you can move on.

I'll recommend to watch the specialization of Neural Network from Andrew Ng, to deeply understand the "magic" ( linear regression, matrices, derivatives) of Neural Networks.

автор: Wei X

Sep 25, 2019

I originally expected to learn more pure TF related stuff. But instead I learned Keras. Data augmentation with Keras is quite easy. Transfer learning is also easy to do if there is Keras model there already. But I do hope to learn a pure TF tutorial that are more common when you download other people's TF model and practice with your own data.

автор: Anil K S

Jun 12, 2019

This was the actual dealing with the dataset saved at local memory location rather than predefine dataset where the dealing with label and directory were ignored which learner actually face problems while learning and handling with the datasets stored at local drive. well this course actually helped for my major year project .

автор: Ara B

Aug 19, 2019

Easy to follow. a lot of examples. I was expecting at least one assignment for the final! :)

As for the convolution we never talked about DOG+SIFT or other feature extraction techniques. Also I would like to see how we can separate an object of interest from background e.g. using clustering or a video stream.

автор: Alvaro M A N

Dec 10, 2019

I love this, because the instructor make the difficult easy. After ending this course, I believe I would enrolled on the other specialization, to gain a better mathematical understanding of convolutional neural networks but I'm pretty happy to learn the practical stuff, this make possible a lot of projects!

автор: Deepak V

May 02, 2020

This course builds on the previous introductory course in the Specialisation. Not only do the four exercises provide practice towards neural network implementation, they also provide a chance to use Python for organisation and manipulation of data, pre-learning.

A fantastic and concise course over all.

автор: Aditya W

Jan 22, 2020

I mainly to learn the various constructs to do various things in TensorFlow, and this course is very well constructed for it. It doesn't explain the actual mathematics though, and I don't blame it for that. It is just designed to help people learn the framework. Overall, a very satisfying experience.

автор: Jian C

May 14, 2020

This course is a very good introduction to Tensorflow and CNN. I have taken Machine Learning theories at school and this is a very nice **programatic** supplement to my course. I think this would be even more helpful if I took it before I learn the theories. I would have been in less trouble then.

автор: Karan S

Apr 11, 2020

It's amazing how far we've come in image processing. I remember using basic filters like sobel edge detector during my undergrad. And now we are here, being able to get SOTA results in just few minutes. I wonder how those Phds who were working on handcrafting filters ~2010 would have felt.

автор: anujeet

Dec 14, 2019

This course in tensorflow specialization is a must recommended. It builds knowledge from beginners to advance very smoothly, You will be able to get a experience of how to begin coding for tensorflow also be able to understand its core layers, And learning from Laurence is always fun.

автор: Sanjay M

Aug 13, 2019

Very well thought through course for Convolution Neural Networks using Tensorflow, covering some of advances topics like transfer learning, callback and review convolution layers. I already had understanding about CNN and these topics. This course shared scenarios when it is used.

автор: Ozgur P

May 02, 2020

Really good course, but recommend doing deeplerning specialization first before doing this one or doing them together. Because Andrew Ng explains really well how convolutions work, and without this background info, it will be difficult to understand the concepts in this course.

автор: Simon Z

Sep 10, 2019

Excellent. I learned after a couple of years working with neural networks new topics and implementations. I think it would be a good idea to include also here an exercise that gets graded at the end such that we take our time and can try out if we can make things work.

автор: Abhinav S T

Jun 22, 2019

The week 1 is a bit casual but where as the remaining one's are just awesome learnt a lot like how to implement a model without overfiting and learnt how to implement transfer learning and multi-class classification problem, really worthy taking up this course....!!!

автор: AKSHAY K C

Apr 06, 2020

The course was nicely built on the advanced topics of multi-class classification, data-augmentation, and transfer learning in Convolutional Neural Networks. Special congratulations to the instructor and his team for coming up with such a nice course.

автор: Mike B

May 11, 2020

The course was excellent. Other than the (typical by now) Coursera code-submission issues, the course really covers a broader range of CV applications & TF capabilities than I've seen with the "get it working and move on" workflow at the day job.

автор: saket p

Jul 01, 2019

This is very well structured course for geeks who want to start learning machine leaning and implement different neural networks are hiking the technology world.

I personally appreciate the course material and instructor for the immense work.

автор: Nebojsa D

Aug 15, 2019

This lectures are givin a very nice advices for practical implementation of ConvNets. combining it with prof.Andrew Ng's lecture exercises in this course will allow you much more practi implementation of knowledge you have acquired before.

автор: Andrés P

Apr 22, 2020

The course in general is pretty good, only the last test seems to me that is incorrect, since there are 24 different classes, but doesn't approve it when you set it with these 24. It requires from you to put 26 when to me seems illogical.

автор: Tanay G

Apr 08, 2020

I found the course really interesting and I learned a lot. The thing I liked the most about this course is the minimal helping nature of the evaluative notebooks, deep learning specialisation's notebooks practically spoon-fed the answers.

автор: arnaud k

Jun 25, 2019

The practical aspect of this course is addicting. I can't stop myself from wanted to try the next technique. maybe because i have seen most of these before but i going had made it clear what i was doing wrong in some of my "failed kaggle"

автор: Jafed E

Jul 06, 2019

I enjoy the lectures. The professor has a good speaking and teaching style which keeps me interested. Lots of concrete math examples which make it easier to understand. Very good slides which are well formulated and easy to understand

автор: Carlos V

Jul 07, 2019

Excellent course, in particular, all explanations to work with the Image Augmentation libraries, I enjoined the transfer learning part, highly recommended for anyone looking to improve their knowledge of Convolutional Neural Networks

автор: Vishakan

Apr 22, 2020

Learnt a lot of new things about image classification, how to better predict images using TensorFlow. Laurence Moroney is a great teacher who skillfully explains the code and its significance in an easy-to-understand manner.

автор: Surya K S

Apr 06, 2020

Incredible course structure. Really well designed and thoughtful. The programming assignments were especially very helpful. Grateful to Coursera for letting me do this specialization during these uncertain times of COVID-19.