Deep Learning for Vision
Get an introduction to deep learning, and apply deep learning to solve problems in computer vision.
1Introduction to Deep Learning
Deep learning intuition
What is Computer Vision and What Makes it Hard
What are Images?
2Neural Networks in Detail
Neural Networks Explained
Forward Propagation
Activation Functions
Loss Functions
Backpropagation and Gradient Descent
Backpropagation & Learning Rates
Regularization, Overfitting, Generalization and Test Datasets
Epochs, Iterations and Batch Sizes
Measuring Performance and the Confusion Matrix
Exhaustive Insights into the Neural Architecture
First Neural Network (Hands-on to custom design a DNN)
Review and Best Practices
3Convolutional Neural Networks (CNN)
Convolutional Neural Networks Introduction
Convolutions & Image Features
Hot One Encoding
Depth, Stride and Padding
ReLU
Pooling
The Fully Connected Layer
Training CNNs
Designing Your Own CNN
Assignment and quiz
4Recurrent Neural Networks (RNN)
5Deep Learning for Vision
Data augmentation
Image classification
Object detection in images
Object detection in videos