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Mastering Computer Vision with Deep Learning: From Basics to Advanced

Unlock the World of Computer Vision: Master Edge Detection, Convolutional Networks, and Advanced Object Recognition in this Transformative Course! Dive into the Heart of AI Innovation with Hands-On Learning and Cutting-Edge Techniques!

4.0 (30)
201 learners

What you'll learn

Understand the fundamental concepts of computer vision and convolutional neural networks.
Learn to implement edge detection, padding, and strided convolutions in image processing.
Explore advanced network architectures like ResNets and Inception networks for improved model performance.
Apply object detection techniques including YOLO algorithm and region proposals for real-world applications.

This course includes

  • 6 hours of video
  • Certificate of completion
  • Access on mobile and TV

Course content

1 modules • 42 lessons • 6 hours of video

Mastering Computer Vision with Deep Learning: From Basics to Advanced
42 lessons • 6 hours
  • C4W1L01 Computer Vision05:44
  • C4W1L02 Edge Detection Examples11:31
  • C4W1L03 More Edge Detection07:57
  • C4W1L04 Padding09:50
  • C4W1L05 Strided Convolutions09:02
  • C4W1L06 Convolutions Over Volumes10:44
  • C4W1L07 One Layer of a Convolutional Net16:10
  • C4W1L08 Simple Convolutional Network Example08:35
  • C4W1L09 Pooling Layers10:29
  • C4W1L10 CNN Example11:40
  • C4W1L11 Why Convolutions09:40
  • C4W2L01 Why look at case studies?03:08
  • C4W2L02 Classic Network18:19
  • C4W2L03 Resnets07:08
  • C4W2L04 Why ResNets Work09:12
  • C4W2L05 Network In Network06:40
  • C4W2L06 Inception Network Motivation10:15
  • C4W2L07 Inception Network08:46
  • C4W2L08 Using Open Source Implementation04:57
  • C4W2L09 Transfer Learning08:48
  • C4W2L10 Data Augmentation09:32
  • C4W2L11 State of Computer Vision12:38
  • C4W3L01 Object Localization11:54
  • C4W3L02 Landmark Detection05:56
  • C4W3L03 Object Detection05:49
  • C4W3L04 Convolutional Implementation Sliding Windows11:08
  • C4W3L06 Intersection Over Union04:19
  • C4W3L07 Nonmax Suppression08:02
  • C4W3L08 Anchor Boxes09:43
  • C4W3L09 YOLO Algorithm07:01
  • C4W3L10 Region Proposals06:27
  • C4W4L01 What is face recognition04:37
  • C4W4L02 One Shot Learning04:45
  • C4W4L03 Siamese Network04:51
  • C4W4L04 Triplet loss15:30
  • C4W4L05 Face Verification06:05
  • C4W4L06 What is neural style transfer?02:12
  • C4W4L07 What are deep CNs learning?08:05
  • C4W4L08 Cost Function04:00
  • C4W4L09 Content Cost Function03:37
  • C4W4L10 Style Cost Function17:01
  • C4W4L11 1D and 3D Generalizations09:08

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