1.
Introduction
2.
Algebra
2.1.
Sieve of Eratosthenes
2.2.
Fibonacci Sequence
2.3.
Linear Diophantine Equations
2.4.
Euler's Totient Function
2.5.
Modular Multiplicative Inverse
3.
Searching Algorithms
3.1.
Linear Search
3.2.
Binary Search
3.3.
Binary vs Linear Search
3.4.
Ternary Search
4.
Sorting Algorithms
4.1.
Bubble Sort
4.2.
Quick Sort
4.3.
Count Sort
4.4.
Bucket Sort
4.5.
Heap Sort
4.6.
Radix Sort
4.7.
Insertion Sort
4.8.
Shell Sort
4.9.
Merge Sort
4.10.
Selection Sort
5.
Backtracking
5.1.
Pseudocode
5.2.
Problems
6.
Persistent Data Structure
6.1.
Persistent Segment Trees
7.
Graph
7.1.
Tree
7.1.1.
Diameter
7.1.2.
Lowest Common Ancestor
8.
String Processing
8.1.
String Hashing
8.2.
Rabin-Karp Algorithm
9.
Machine Learning Algorithms
9.1.
Regression
9.1.1.
Linear Regression
9.1.1.1.
Linear Regression using Scikit-Learn
9.1.1.2.
Linear Regression using Matrix Multiplication
9.1.1.2.1.
One Variable Linear Regression
9.1.1.2.2.
Multiple Variable Linear Regression
9.2.
Deep Learning
9.2.1.
Neural Network
Light (default)
Rust
Coal
Navy
Ayu
Algorithms
Machine Learning Algorithms
These are the engines of Machine Learning.
Topics Covered
Regression
Linear Regression
Linear Regression using Scikit-Learn
Linear Regression using Matrix Multiplication
One Variable Linear Regression
Multiple Variable Linear Regression
Deep Learning
Neural Network