Book Content
chapters • 27h28m total length
1. Artificial Neural Network Fundamentals
2. PyTorch Fundamentals
3. Building a Deep Neural Network with PyTorch
4. Introducing Convolutional Neural Networks
5. Transfer Learning for object Classification
6. Practical Aspects of Image Classification
7. Basics of Object detection
8. Advanced object detection
9. Image segmentation
10. Applications of object detection and localization
11. Autoencoders and Image Manipulation
12. Image generation using GAN
13. Advanced GANs to manipulate images
14. Training with minimal data points
15. Combining Computer Vision and NLP techniques
16. Combining Computer Vision and Reinforcement Learning
17. Moving a Model to Production
18. OpenCV utilities for image analysis
