# Outline:

1. Definition of the Image Segmentation
2. What is K-Means?
3. How to perform the image segmentation with the K-Means clustering algorithm?

# What is Image Segmentation?

## What is an image?

An image expresses the visual information. They are saved on our computers as tensors. They can be in a dimension of 2D, 3D and etc. For instance, let’s take the example of the Gandalf picture.

We can see exactly as it is, but how do the computers see them? As tensors?

# Fourier Series and Fourier Transform. Signal Denoising.

Outline:

1. Fourier Series
2. Fourier Transform
3. Signal Denoising using the Fourier transform

# Fourier Series

Fourier series helps us define any periodic function as the sum of the sine and cosine functions. Also, it helps us to get the amplitude and phase spectrum. First of all, let’s have a look at the mathematical expression of the Fourier Series.

Fourier Series provides the decomposition of the periodic function on a base of the harmonic functions.

The given formula expresses the coefficients of the Fourier series. We can derive the equations related to the function. They can change regards to the demanding question.

We can propose another way of the Fourier Series…

# Outline:

1. Some New Terminologies
2. Euler, Hamiltonian, and Bipartite graphs
4. Depth-First Search

# Some New Terminologies

1. The null Graph does not contain any edge. There is no connection between the vertices.

2.The possible smallest graph is the trivial graph which contains only one vertex.

# Motivation

Question1: Which Data Structure would you use to implement the navigation app from scratch?

Question2: We have the following flight diagram. The numbers express the flight prices in hundred dollars. Could you say the cheapest way to go from Berlin to Minsk?

# Derivation of the Normal Equation of Linear Regression problem

Linear Regression is the prediction of the continuous labels which finds the line fits best to the data points that plotted on the cartesian coordinate system.

Here is the example of the data points that illustrate the relationship between the years of experience and salary. Everything we need to define the best linear formula that expresses all these points.

Here is the line that fits the data points given above. Different optimization algorithms can be applied to fins the linear formula, like Stochastic Gradient Descent, Batch Gradient Descent and etc. … 