# Smoothing Images using OpenCV

Today I am back with a new article. I am writing this article because I had started with this topic to learn when I was new to OpenCV. In this article, I am trying to explain the noise removal techniques. I hope you will enjoy reading it.

2. Image Blurring
• Averaging
• Gaussian Filtering
• Median Filtering

2D Convolutional:

What is Convolutional in Image Processing?

It is a simple mathematical operation between two arrays of numbers, different sizes, but the same dimensionality to produce the third. The convolution happens between…

# Deploying a Machine Learning Model using Flask for Beginners

The deployment of the machine learning model is rarely discussed. Most of the data science programs, online courses do not focus on model deployment. It is one of the important and last stages in the machine learning life cycle. To start using your machine learning model for practical decision-making, it needs to be effectively deployed into production. The focus of this article is to deploy a machine learning model using a flask.

Here I am using mall customer dataset to understand customer behavior. We are going to build a clustering model on historic data. …

# Ordinary Least Square (OLS) Method for Linear Regression

This post is about the ordinary least square method (OLS) for simple linear regression. If you are new to linear regression, read this article for getting a clear idea about the implementation of simple linear regression. This post will help you to understand how simple linear regression works step-by-step.

The simple linear regression is a model with a single regressor (independent variable) x that has a relationship with a response (dependent or target) y that is a

y = β0 + β1 x + ε — — — — — — — — — — (1)

Where β0: intercept

β1…

# Implementation of Stochastic Gradient Descent

The purpose of writing this post is to understand the maths behind gradient descent. Most of us are using gradient descent in machine learning, but we need to understand the maths behind it.

As a fresher, when I was learning stochastic gradient descent, I found it a little bit complex. Here, I tried to make it simpler for those who want to know how it works.

My focus on this post is to demonstrate the mathematics behind gradient descent.

Take a quick refresher on what is gradient descent?

Gradient Descent: It is an optimization technique that is used to find…

# Everything about Components of Time Series: Part-1

Time series analysis is not an easy topic, I must say. At least for me. During my graduation, I had the chance to learn the subject, and it took me some time to get my head around it. The purpose of this article is to energize what I have learned and trying to explain to others.

You will enjoy time series analysis if you know the real-life use of time series. Let’s see the use of time series in real life.

Time Series in Real Life:

• It enables us to study the past behaviour of the phenomenon under consideration, i.e…

## Aishwarya Gulve

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