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
Offered By


About this Course
Intermediate Python skills: basic programming, understanding of for loops, if/else statements, data structures
A basic grasp of linear algebra & ML
Skills you will gain
- Deep Learning
- Facial Recognition System
- Convolutional Neural Network
- Tensorflow
- Object Detection and Segmentation
Intermediate Python skills: basic programming, understanding of for loops, if/else statements, data structures
A basic grasp of linear algebra & ML
Offered by
Syllabus - What you will learn from this course
Foundations of Convolutional Neural Networks
Deep Convolutional Models: Case Studies
Object Detection
Special Applications: Face recognition & Neural Style Transfer
Reviews
- 5 stars87.75%
- 4 stars10.35%
- 3 stars1.43%
- 2 stars0.28%
- 1 star0.17%
TOP REVIEWS FROM CONVOLUTIONAL NEURAL NETWORKS
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.
A big thank you to Professor Andrew and his team for structuring this course and introducing the world of ConvNets to me. I found the video lectures easy to understand and the exercises intriguing.
Too much hand-holding during assignments, although still very good directions. Obviously the issue with the final programming assignment needs to be addressed. Fantastic lecture material, as always.
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.
About the Deep Learning Specialization

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