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Learner Reviews & Feedback for Advanced Computer Vision with TensorFlow by DeepLearning.AI

4.8
stars
502 ratings

About the Course

In this course, you will: a) Explore image classification, image segmentation, object localization, and object detection. Apply transfer learning to object localization and detection. b) Apply object detection models such as regional-CNN and ResNet-50, customize existing models, and build your own models to detect, localize, and label your own rubber duck images. c) Implement image segmentation using variations of the fully convolutional network (FCN) including U-Net and d) Mask-RCNN to identify and detect numbers, pets, zombies, and more. d) Identify which parts of an image are being used by your model to make its predictions using class activation maps and saliency maps and apply these ML interpretation methods to inspect and improve the design of a famous network, AlexNet. The DeepLearning.AI TensorFlow: Advanced Techniques Specialization introduces the features of TensorFlow that provide learners with more control over their model architecture and tools that help them create and train advanced ML models. This Specialization is for early and mid-career software and machine learning engineers with a foundational understanding of TensorFlow who are looking to expand their knowledge and skill set by learning advanced TensorFlow features to build powerful models....

Top reviews

EN

Sep 30, 2021

I have learnt many useful computer vision algorithms and more importantly applied them myself. In my mind, practical sessions provided during the course makes it one of the best in Coursera platform

LD

Mar 22, 2023

This course is amazing. It is introduced the most important topics in Computer Vision nowadays: from object detection to generative networks. This is a must-to-do in any capacitation on AI field.

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26 - 50 of 74 Reviews for Advanced Computer Vision with TensorFlow

By Gisha G S

Oct 27, 2022

course content was very informative.Learned the concepts with practical experience.Great Learning!!!!

By Eduardo R

Oct 17, 2022

The course haves great documents, there you can find everything you'll need to improve your models.

By Nikolay S

Feb 28, 2021

This course was fantastic! Laurence and DeepLearning.ai team did great job. Definitely recommended.

By Rawan L

Jan 20, 2021

This course was super useful cause it's practical and not only focusing on the theory part.

By Wong H S

Feb 11, 2021

Excellent content, learnt a lot and gain deeper insight into computer vision techniques.

By Faizan S

Feb 11, 2021

The whole course was very good! Especially week 4, learned some new concepts in week 4.

By Nitin K

Apr 13, 2021

It is awesome course. Direct to the point with great depth in subject.

By USEYD K

Jan 16, 2023

it was a good thing for those who want to get into the word of cv.

By Serge T

Feb 8, 2021

Good course, lots of useful information, great practical exercises!

By GOPU V R M K 1

Apr 22, 2021

Fantastic course on Advanced Computer Vision with Tensorflow.

By Mohammed Z D

Dec 5, 2021

It's the most fascinating course so far. Thank you so much.

By Belaid C

May 22, 2021

Tank you. I have learned a lot of technical skills

By Olexander A

Nov 29, 2021

Great course! But CV models is soooo expensive :D

By Animesh

Feb 7, 2021

nicely designed course. great instructor too! : )

By Aleksandr S

Jan 31, 2021

Excellent course with theory and practical tests.

By 西川 尚之

Jan 15, 2021

This course is very exciting and useful ! Great!

By Abrar H

Sep 28, 2024

The perfect balance of Theory and Practice.

By Ed H C

Jan 23, 2021

I'm hoping to apply this on my own project.

By Syed N H

Feb 6, 2021

One of the best course I have ever done <3

By Duc A L

Oct 25, 2021

This course can upgrade your skills

By Shafique K

Sep 5, 2021

New learning in my learning bucket.

By Ali E

Aug 19, 2021

so informative and practical course

By Aleksander Z

Feb 21, 2021

Very usefull course. Thanks!

By HABIB M

Mar 31, 2021

it's a very good courses

By Jorge S

Mar 29, 2021

Best content around !