In the fourth course of the Deep Learning Specialization, you will understand how computer vision has evolved and become familiar with its exciting applications such as autonomous driving, face recognition, reading radiology images, and more.
Convolutional Neural Networks
Convolutional Neural Networks
This course is part of Deep Learning Specialization
Instructors: Andrew Ng
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Gain insight into a topic and learn the fundamentals.
4.9
(42,511 reviews)
Intermediate level
Recommended experience
Flexible schedule
4 weeks at 10 hours a week
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Assessments
4 assignments
Taught in English
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This course is part of the Deep Learning Specialization
When you enroll in this course, you'll also be enrolled in this Specialization.
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There are 4 modules in this course
Implement the foundational layers of CNNs (pooling, convolutions) and stack them properly in a deep network to solve multi-class image classification problems.
What's included
12 videos6 readings1 assignment2 programming assignments
Discover some powerful practical tricks and methods used in deep CNNs, straight from the research papers, then apply transfer learning to your own deep CNN.
What's included
14 videos3 readings1 assignment2 programming assignments
Apply your new knowledge of CNNs to one of the hottest (and most challenging!) fields in computer vision: object detection.
What's included
14 videos4 readings1 assignment2 programming assignments
Explore how CNNs can be applied to multiple fields, including art generation and face recognition, then implement your own algorithm to generate art and recognize faces!
What's included
11 videos6 readings1 assignment2 programming assignments
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4.9 (3,223 ratings)Offered by
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4.9
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Showing 3 of 42511
DD
5
Reviewed on Feb 6, 2020
very easy to understand and helped my understanding in Deep Learning-based computer vision. Yet, this course will need to be updated with new developments in the future (to catch up with the trend).
FH
5
Reviewed on Jan 11, 2019
Amazing! Feels like AI is getting tamed in my hands. Course lectures , assignments are excellent. To those who are not well versed with python - numpy and tensorflow , it would be better to brush up.
SB
5
Reviewed on Jul 15, 2020
For me personally it's the best course in Deep Learning specialization. Well structured, interesting projects, good examples! The only thing that could be better is to use Tensorflow 2 instead of 1.0
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Frequently asked questions
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