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Learner Reviews & Feedback for Convolutional Neural Networks in TensorFlow by DeepLearning.AI

4.7
stars
8,024 ratings

About the Course

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....

Top reviews

MS

Nov 12, 2020

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!

RB

Mar 14, 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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876 - 900 of 1,245 Reviews for Convolutional Neural Networks in TensorFlow

By 4SF18IS103 - S A

Apr 8, 2020

I really did enjoy learning and playing around with the workbooks, however the exercise problems needed more explanation as how to go about since sometimes some of the concepts are not very obvious unless we dig into the documentation of the tensor flow and keras libraries which can be a good thing.

By William C

Aug 18, 2021

It's a good introduction, and the consistency of a well structured course in general is fantastic. Some of the graded pieces are you simply rewriting code that they've already shown you. I would have liked some quizzes on the correct keras function calls to drill it in to my memory.

By Anson L

Mar 31, 2023

Everything is fine, detail explanation of concepts, step by step tutorial making me feeling good and learn the tensorflow in a proper speed. This is a great course!

I am not sure but the final assignment in week 4 seems has bug but I couldn't amend other code. regarding the labels.

By Narayana S

Mar 17, 2020

Good coverage of practical stuff in image recognition but it only covers the basic introductory stuff. There is a lot more to image recognition than what Is covered in this course. This will give a foundation to a novice user to learn more advanced deep learning techniques.

By Henk M

Dec 22, 2019

This course explores the topics of the first course for image classification with neural networks. All the tests are multiple choice questions. There are some code examples to work with as well as extra exercises but it would have been good to have a programming test as well.

By Arda G

Apr 1, 2021

This course is great for those needing an introduction to convolutional neural networks. It would be truly amazing if there were more tutorials on transfer learning. It is not quite possible to fluently use pre-trained models only with the knowledge offered in this course.

By Jeff C

Feb 15, 2022

If there is more coverage on the concept behind the augmentation parameters and how to tune the value, then that would be even better. Now I think most of the students just adjust the parameter value with trial and error approach in order to fulfill the accuracy target

By Przemek D

Jun 14, 2020

Generally a really good course, but the last assignment is out of nothing very badly explained in terms of data processing, which causes the grader to fail or run out of memory and therefore passing it is quite a challenge. Besides that, a very good intro to CNNs.

By Faiz A

Aug 2, 2020

Course was quite good, but the last assignment was a little challenging,Well..that's what i really liked!. Also, i felt like more concepts in computer vision had to be covered like Object detection, segmentation. Fairly basic concepts were emphasized here.

By Pranjal J

Dec 12, 2021

This course provided a nice guidance about filtering, cleaning and augmenting the datasets. This will definately help to build the models where the custom dataset needs to be generated and then use it for training with reduced chances of overfitting.

By Marco

Jul 25, 2020

I think some parts of the assignments are not really the main objective of the course, they focus more on methods that involve just creating folders and copying files, which is not what I was there for. Aside from that, great ML content right here :)

By Oscar D D L T

Sep 7, 2020

Excelente curso, casi no necesitas saber programar los conceptos super actuales y las actividades te permiten ejecutar procesos de inteligencia artificial y lograr resultados interesantes con un conocimiento tecnico minimo....super recomandable!!!!!

By Saeif A

Aug 20, 2019

This is another great course in the specialization. I wish only there were graded exercises like the previous course that we can submit and get a grade for. I understand maybe this is due to the long time of training and that is not possible to do.

By Voltaire L

Jan 15, 2021

The final project was missing some prompts for additional code. I'm all for research but there should be a heads up that we won't have all the prompts we need, since all the tests before specifically asked for the code needed to pass.

By Thomas L

Nov 4, 2019

Maybe a bit repetitive, when you just finished Course 1. We see a lot of lines of codes explained again from course 1 and I think that could be avoided.

However, the new concepts are nicely introduced and very interesting to implement!

By Alvin M

Oct 27, 2020

Sudden spike of difficulty and approach in the final assignment, but overall, the pacing is really nice. You really can't solve the last assignment without reading the discussion forum or looking for things for yourself though.

By William G

Aug 16, 2019

It was good, but similar to other learners I feel a little light in content. Though in tandem with the deep learning specialization gives a good view on convolutional neural networks as well as its implementation in tensorflow.

By masha A

Dec 18, 2022

I wouldn't say that I learned a lot more than from the 1st course (Intro to Tensorflow). I would also have appreciated a deeper dive into the theory of CNNs, because otherwise the programming assignments turn into a copy-pase

By thingsofleon

Oct 26, 2019

Loved the course. I would have liked a module on saving your own models and then loading them later. The Inception one is nice, but it comes with some "niceties" that I don't think you have with loading a home grown model.

By Humberto N

Jun 9, 2019

It's an great course with simple explanations about the Deep Learning topic. It's a perfect fit for beginners or those who want to have a practical review before starting using Tensorflow 2.0 with keras implemetations.

By Varun K M

Apr 27, 2020

It was a great course but there wasn't much theory into explaining why and what's happening. A course to get started with the coding without actually needing to require what is happening in the background.

By J N B P

Jan 26, 2021

A great course for those who want to start building their AI models using Tensorflow. It explains how to use the required tools for different purposes like data augmentation, transfer learning, etc.

By Kalana A

Apr 14, 2020

Nice course. Even though I have previously done some projects using CNN and multi-class classification still this course let me to have an insight to how these APIs work. Keep Up The Good Work!!!!!!

By Fahmi J

Apr 29, 2020

This course awesome, but the notebook from coursera "i think" doesn't support any experiment we want, so we have to do it on google colab. But great, limitation is okay as long it's still graded

By XX N

Oct 2, 2019

The course is really nice. But would be better if the convolutional layers were a bit more detailed. It was a bit difficult for me to understand all the parameters e.g: input/output filter size.