- 01. Deep Learning at NVIDIA
- 02. Classifying Sebastian
- 03. Welcome to Computer Vision
- 04. Introducing Tarin
- 05. Vision and Self-Driving Cars
- 06. LiDAR Data
- 07. Image Classification Pipeline
- 08. Quiz: Classification Steps
- 09. Learning to Classify Images
- 10. What is Machine Learning?
- 11. Training a Model
- 12. Quiz: Choose Layers of Separation
- 13. Images as Grids of Pixels
- 14. Notebook: Images as Numerical Data
- 15. Color Images
- 16. Color or Grayscale?
- 17. Notebook: Visualizing RGB Channels
- 18. Pre-processing
- 19. Notebook: Cropping and Resizing
- 20. Color Masking
- 21. Installing OpenCV, Instructions
- 22. Green Screen Car
- 23. Notebook: Green Screen Background
- 24. Color Spaces and Transforms
- 25. HSV Conversion
- 26. Notebook: Color Conversion
- 27. Day and Night Classification
- 28. Notebook: Load and Visualize the Data
- 29. Labeled Data and Accuracy
- 30. Distinguishing Traits
- 31. Feature Extraction
- 32. Features
- 33. Standardizing Output
- 34. Notebook: Standardizing Day and Night Images
- 35. Average Brightness
- 36. Notebook: Average Brightness Feature Extraction
- 37. Features and Classification
- 38. Selecting Features
- 39. Filters and Finding Edges
- 40. High-pass Filter
- 41. Quiz: Kernels
- 42. Notebook: Finding Edges
- 43. Convolution in Self-Driving Cars
- 44. Notebook: Histograms and Feature Vectors
- 45. Classification
- 46. Notebook: Classification
- 47. Convolutional Neural Networks
- 48. Evaluation Metrics
- 49. Notebook: Accuracy and Misclassification
- 50. Congratulations!!
- 51. Ends and Beginnings!