Data Science
TECHNIQUES FOR GENERATING RANDOM NUMBERS
Test for Random numbers
Tests for Autocorrelation
Linear Congruential Method in R & Chi-square Test in R |
Monte Carlo simulation
Fundamental of Data Science
Graph Theory (Part-I)
Subgraphs, Spanning Subgraphs, Operation on Graphs
Walk, Trails, Path and connected Graphs
At most number of edges with n vertices and k component
Cycle in Graph
Euler Graph and Hamiltonian Graph
Tree
Theorem on Tree, Spanning Tree and Fundamental circuits
Dijkstra's algorithm (Example)
Floyd-Warshall's Algorithm
Dijkstra's Algorithm (examples-2)
Floyd-Warshall's Algorithm (Example-2)
Kruskal's Algorithm and Prim's Algorithm
Breadth First Search Algorithm
Matrix Representation on Graph
Adjacency Matrix
The Law of Large Numbers
High Dimensional object is that Most of their volume is near the surface
Volume of the Unit Ball in d-dimensional space
Most of the volume is near equator
Near Orthogonality, Generating points Uniformly & Gaussians in High Dim. |
Random Projection & Johnson-Lindenstrauss Lemma
Separating Gaussian
Degree Distribution in G(n,p) model
Existence of triangle in G(n,d/n) model
First & Second Moment Methods , Phase transition
Threshold for graph diameter Two
Disappearance of Isolated Vertices
Hamilton Circuits and The Giant component
Emergence of cycle
Giant Component in Random Graphs with Given Degree Distribution
Power Method
Small world Graph
Singular value Decomposition
Image compression using SVD
Images and Matrices
Minimum length solution
Random Walk (Part-I)
Random numbers generaration
The Monte Carlo simulation