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In this course, you will learn :
- Convolutional Neural Networks
- Image Processing
- Advance Deep Learning Techniques
- Regularization, Normalization
- Transfer Learning
Syllabus :
1. Convolutional Neural Networks
- What is image
- Motivation to Convolutions
- Convolution operation
- Parameters of the convolution
- Non-linear function
- Max Pooling and Average Pooling
- Building deep convolutional network
2. Regularization and Normalization
- Overfitting. L2 regularization
- DropOut regularization. DropConnect regularization
- DropBlock regularization
- Early Stopping regularization
- Batch Normalization
3. Improving the quality
- Data Augmentation
- Existing datasets
- Modern Architectures
- Transfer Learning
4. Boat Recognition Project
- Data Loading
- Data Augmentation
- Transfer Learning: ResNet-18
