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.
This course is part of the Deep Learning Specialization
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Deep Learning SpecializationDeepLearning.AIAbout this Course
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Course 4 of 5 in the
Intermediate Level
- Intermediate Python skills: basic programming, understanding of for loops, if/else statements, data structures
- A basic grasp of linear algebra & ML
Approx. 39 hours to complete
English
Subtitles: Chinese (Traditional), Arabic, French, Portuguese (European), Chinese (Simplified), Italian, Vietnamese, Korean, German, Russian, Turkish, English, Spanish, Japanese
Skills you will gain
- Deep Learning
- Facial Recognition System
- Convolutional Neural Network
- Tensorflow
- Object Detection and Segmentation
Flexible deadlines
Reset deadlines in accordance to your schedule.
Shareable Certificate
Earn a Certificate upon completion
100% online
Start instantly and learn at your own schedule.
Course 4 of 5 in the
Intermediate Level
- Intermediate Python skills: basic programming, understanding of for loops, if/else statements, data structures
- A basic grasp of linear algebra & ML
Approx. 39 hours to complete
English
Subtitles: Chinese (Traditional), Arabic, French, Portuguese (European), Chinese (Simplified), Italian, Vietnamese, Korean, German, Russian, Turkish, English, Spanish, Japanese
Offered by
DeepLearning.AI
DeepLearning.AI is an education technology company that develops a global community of AI talent.
Syllabus - What you will learn from this course
11 hours to complete
Foundations of Convolutional Neural Networks
Implement the foundational layers of CNNs (pooling, convolutions) and stack them properly in a deep network to solve multi-class image classification problems.
11 hours to complete
12 videos (Total 140 min), 6 readings, 5 quizzes
10 hours to complete
Deep Convolutional Models: Case Studies
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.
10 hours to complete
14 videos (Total 127 min), 1 reading, 4 quizzes
10 hours to complete
Object Detection
Apply your new knowledge of CNNs to one of the hottest (and most challenging!) fields in computer vision: object detection.
10 hours to complete
14 videos (Total 110 min), 3 readings, 4 quizzes
9 hours to complete
Special Applications: Face recognition & Neural Style Transfer
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!
9 hours to complete
11 videos (Total 75 min), 5 readings, 4 quizzes
Reviews
TOP REVIEWS FROM CONVOLUTIONAL NEURAL NETWORKS
by RKSep 1, 2019
This is very intensive and wonderful course on CNN. No other course in the MOOC world can be compared to this course's capability of simplifying complex concepts and visualizing them to get intuition.
by ARJul 11, 2020
I really enjoyed this course, it would be awesome to see al least one training example using GPU (maybe in Google Colab since not everyone owns one) so we could train the deepest networks from scratch
by RSDec 11, 2019
Great Course Overall One thing is that some videos are not edited properly so Andrew repeats the same thing, again and again, other than that great and simple explanation of such complicated tasks.
by AGJan 12, 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.
About the Deep Learning Specialization
The Deep Learning Specialization is a foundational program that will help you understand the capabilities, challenges, and consequences of deep learning and prepare you to participate in the development of leading-edge AI technology.
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