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In Machine Learning I, we observed the prediction success of our models and how the process was. We continue.

Least Square Method

This method is generally used in libraries such as scikit-learn, scipy, and regression problems. Gradient descent method is not used in these libraries.
The Normal Equations method gives us…


Machine learning is a branch of artificial intelligence (AI) and computer science which focuses on the use of data and algorithms to imitate the way that humans learn, gradually improving its accuracy.

Basic Concepts:

1- Variables

It is divided into dependent and independent variables. Dependent variables can be named as a target, dependent, output…


Feature engineering is the process that takes raw data and transforms it into features that can be used to create a predictive model using machine learning or statistical modeling, such as deep learning. Feature engineering aims to prepare an input data set that best fits the machine learning algorithm and…


What Is A/B Testing?

A/B testing (also known as split testing or bucket testing) compares two versions of a web page or app against each other to determine which one performs better. AB testing is essentially an experiment where two or more variants of a page are shown to users at random. …


With the development of technology, our habits are also changing. As such, most of today’s E-Commerce sites use their own proprietary recommendation algorithms to better serve customers with the products they have to like. There are many examples such as Netflix’s movies, Spotify’s music, Facebook recommending friends, product recommendations of…


Association Rule was one of the first techniques used in data mining. Today, these rules are also referred to as the “Recommendation System.” It aims to make predictions about future sales by analyzing the patterns of transactions in the past and using this information. It is a rule-based machine learning…


In this article, I will discuss the ways to reveal this potential value.

This is the second and the final part of the article series about Customer Value. In the first part, I discussed the core of customer value calculation: RFM metrics and scores.

This final part will be about…


Hello everyone! I am back with another article. This post will describe RFM analysis and show how to use it for customer segmentation by analyzing an online retail shop’s data set on python. …


Rule-Based Classification

In this article, we will do a simple rule-based segmentation study using only pandas functions without using machine learning.

We will create new customer definitions (level-based persona) by using the user information we have and the information about the purchases made by the users. …


What is virtual environment?

At its core, the main purpose of Python virtual environments is to create an isolated environment for Python projects. This means that each project can have its own dependencies, regardless of what dependencies every other project has.

Tools with functionality to create and manage virtual environments:

  • venv (part of the…

Berkay

Data Science Enthusiast — For more information check out my LinkedIn page here: www.linkedin.com/in/berkayihsandeniz

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