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Convolutional Neural Networks,



This course will teach you how to build convolutional neural networks and apply it to image data. Thanks to deep learning, computer vision is working far better than just two years ago, and this is enabling numerous exciting applications ranging from safe autonomous driving, to accurate face recognition, to automatic reading of radiology images. You will: - Understand how to build a convolutional neural network, including recent variations such as residual networks. - Know how to apply convolutional networks to visual detection and recognition tasks. - Know to use neural style transfer to generate art. - Be able to apply these algorithms to a variety of image, video, and other 2D or 3D data. This is the fourth course of the Deep Learning Specialization....


by AG

Jan 13, 2019

Great course for kickoff into the world of CNN's. Gives a nice overview of existing architectures and certain applications of CNN's as well as giving some solid background in how they work internally.

by EB

Nov 03, 2017

Wonderful course. Covers a wide array of immediately appealing subjects: from object detection to face recognition to neural style transfer, intuitively motivate relevant models like YOLO and ResNet.



by Hagay Gur

Apr 26, 2019

Course is very informative.

Unfortunately, unlike other courses in the spec, there were quite a few bugs in the notebooks and they took quite a while to load due to the sheer weight of the models loaded.

by Gyuho Song

Apr 25, 2019

This course is definitely tougher than the first three courses. Challenging but worth it.

by Antreas Koutroumpis

Apr 25, 2019

A fantastic convolutional neural networks course! Andrew Ng is a great tutor. I felt ready to implement my ideas on CNNs immediately after completing this course.

by Molly Zhang

Apr 25, 2019

It's a really great course covering important concepts in CNN such as residual network, face recognition, neural style transfer and other very captivating topics. The only complaints I have about this course is that the programming assignments are a little too simple, most of it is already done and we are only required to do a very small part. I would have enjoyed more challenging homework.

by Miroslav Muras

Apr 24, 2019

I've gained very important knowledge for Image verification and recognition algorithms using ConvNet models. These models are used nowadays powering robots and self-driving cars. Thank you very much for this opportunity to get closer to finishing my new carrier journey.

by Shimin Zhang

Apr 24, 2019

nice courses

by Марчевский Владислав Дмитриевич

Apr 24, 2019

Greate one!

by Pedro Brandimarte Mendonca

Apr 24, 2019

ConvNets is an amazing topic. The course has strong hands on characteristic, with nice intuitive explanations of every algorithm. I particularly liked the choices for the applications and the nice recommendations for the reference papers.

by Sergio Leonardo Mendes

Apr 23, 2019

Excellent Course!

by Mohammed Khursheed Ali Khan

Apr 23, 2019

Intuitions for neural style transfer are a amazing