Aug 3, 2021Machine Learning IIIn 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…Linear Regression2 min read
Aug 3, 2021Machine Learning IMachine 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…Machine Learning7 min read
Jul 13, 2021Feature Engineering for Machine LearningFeature 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…Feature Engineering6 min read
Jun 20, 2021A/B TestingWhat 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. …Ab Testing3 min read
Jun 13, 2021Hybrid Recommender SystemWith 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…Recommendation System4 min read
Jun 13, 2021Market Basket Analysis Using Association RulesAssociation 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…Association Rule2 min read
Jun 8, 2021Customer Life Time Value (CLTV)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…Cltv3 min read
Jun 6, 2021Customer Segmentation with RFM AnalysisHello 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. …Rfm Analysis4 min read
Jun 1, 2021Level Based Persona and SegmentationRule-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. …Data Science2 min read
May 24, 2021Creating Python Virtual Environment and Managing DependencyWhat 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…Pyhton2 min read
