Convolutional Neural Networks (Course 4 of the Deep Learning Specialization)
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!
5.0
(3)
45 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
Mastering Computer Vision with Deep Learning: From Basics to Advanced
42 lessons
• 6 hours
- C4W1L01 Computer Vision 05:44
- C4W1L02 Edge Detection Examples 11:31
- C4W1L03 More Edge Detection 07:58
- C4W1L04 Padding 09:50
- C4W1L05 Strided Convolutions 09:02
- C4W1L06 Convolutions Over Volumes 10:45
- C4W1L07 One Layer of a Convolutional Net 16:11
- C4W1L08 Simple Convolutional Network Example 08:35
- C4W1L09 Pooling Layers 10:30
- C4W1L10 CNN Example 11:40
- C4W1L11 Why Convolutions 09:41
- C4W2L01 Why look at case studies? 03:08
- C4W2L02 Classic Network 18:19
- C4W2L03 Resnets 07:08
- C4W2L04 Why ResNets Work 09:13
- C4W2L05 Network In Network 06:40
- C4W2L06 Inception Network Motivation 10:15
- C4W2L07 Inception Network 08:46
- C4W2L08 Using Open Source Implementation 04:57
- C4W2L09 Transfer Learning 08:48
- C4W2L10 Data Augmentation 09:32
- C4W2L11 State of Computer Vision 12:38
- C4W3L01 Object Localization 11:54
- C4W3L02 Landmark Detection 05:57
- C4W3L03 Object Detection 05:49
- C4W3L04 Convolutional Implementation Sliding Windows 11:09
- C4W3L06 Intersection Over Union 04:19
- C4W3L07 Nonmax Suppression 08:02
- C4W3L08 Anchor Boxes 09:43
- C4W3L09 YOLO Algorithm 07:02
- C4W3L10 Region Proposals 06:28
- C4W4L01 What is face recognition 04:38
- C4W4L02 One Shot Learning 04:45
- C4W4L03 Siamese Network 04:52
- C4W4L04 Triplet loss 15:30
- C4W4L05 Face Verification 06:06
- C4W4L06 What is neural style transfer? 02:13
- C4W4L07 What are deep CNs learning? 08:05
- C4W4L08 Cost Function 04:00
- C4W4L09 Content Cost Function 03:38
- C4W4L10 Style Cost Function 17:01
- C4W4L11 1D and 3D Generalizations 09:09
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