# Summary

M4, M5,
P2,
Q5, Q6, Q7, Q8,

# Lectures

Lecture 5: Slides.
Lecture 6: Slides.
Lecture 7: Slides.
Lecture 8: Slides.

Lecture 5 Part 1 (Support Vector Machines): Link
Lecture 5 Part 2 (Subgradient Descent): Link
Lecture 5 Part 3 (Kernel Trick): Link
Lecture 6 Part 1 (Decision Tree): Link
Lecture 6 Part 2 (Random Forrest): Link
Lecture 6 Part 3 (Nearest Neighbor): Link
Lecture 7 Part 1 (Convolution): Link
Lecture 7 Part 2 (Gradient Filters): Link
Lecture 7 Part 3 (Computer Vision): Link
Lecture 8 Part 1 (Computer Vision): Link
Lecture 8 Part 2 (Viola Jones): Link
Lecture 8 Part 3 (Convolutional Neural Net): Link


Image by Vishal Arora via medium

# Other Materials

Support Vector Machine: Link
Kernel Trick Video: Link
RBF Kernel SVM Demo: Link
Art or garbage game: Link
Decision Tree: Link
Random Forrest Demo: Link
K Nearest Neighbor: Link
Map of Manhattan: Link
Voronoi Diagram: Link
KD Tree: Link
Conv Net on MNIST: Link
Conv Net Vis: Link
Jay's Conv Net Vis: Link
LeNet: Link
Image segmentation: Link, Link, Link
Image colorization: Link, Link, Link 
Image Reconstruction: Link
Drawing to Images: Link
Style Transfer: Link, Link
Move Mirror: Link
Pose Estimation: Link, Link
YOLO Attack: Link
Image Filter: Link
Canny Edge Detection: Link
SIFT: PDF
HOG: PDF
LeNet: PDF
Google Inception Net: PDF
CNN Architectures: Link
CNN Architectures: Link
Super resolution: Link

How to find the margin expression for SVM? Link
Why does the kernel trick work? Link
Example (Quiz): Compute SVM classifier Link
Example (Quiz): Kernel SVM for XOR operator Link
Example (Quiz): Kernel matrix to feature vector Link
Example (Quiz): Entropy computation Link
Example (Quiz): Decision tree for implication operator Link
Example (Quiz): Three nearest neighbor Link
How to find the HOG features? Link
How to count the number of weights for training for a convolutional neural network (LeNet)? Link
Example (Quiz): How to find the 2D convolution between two matrices? Link
Example (Homework): How to find a discrete approximate Gausian filter? Link