Clustering

Introduction In this report, we present the findings and insights from a customer segmentation project conducted for Arvato Financial Services. The objective of the project was to analyze demographic data provided by Bertelsmann Arvato Analytics and identify distinct customer segments. …

TL;DR: A brief intro to the captivating world of clustering, where data sorting becomes as simple yet crucial as sorting laundry, enabling personalised customer experiences across diverse sectors. This post focuses on business understanding and use cases, while technical details will be covered in upcoming posts! Clustering, a technique used…

Table of Contents Introduction What is MQTT Broker, and Cluster? Why MQTT Broker Clustering? What Will Be Explored in This Series? Wrapping Up Introduction Welcome to the first post in our new series exploring the world of MQTT broker clustering. If you’re involved in the IoT (Internet of Things) space or…

About SOMs Introduced by Finnish professor Teuvo Kohonen in the 1980s, Self-Organizing Maps or SOMs provide a means for lower dimensional and discretized representation, called a ‘map’, of datasets while retaining the topology of the data. The goal is to learn a map which responds in a similar way to alike input…

A Comprehensive Journey: Extract, Transform, Model, and Visualize A Step-by-Step Guide to Building a Customer Segmentation Dashboard in PowerBI using PyCaret Introduction Customer segmentation is a powerful technique that groups customers based on their similarities. It is a popular technique used by marketers to understand their customers better and to improve…

In this installment of a 3 Part Series, we will walk step-by-step through everything you need to know to understand K-Means Clustering: Part 1: The Basics Basics: Understanding clustering, Euclidean Distances etc. Intuition: A Visual Walkthrough of K-Means in Action Part 2: Coding the Algorithm from Scratch Algorithm: Formal Overview Code Implementation: Python Implementation from Scratch Part 3: Real Life Implementation

In the previous article we dwell into Word2vec Model in https://medium.com/@aneesha161994/clustering-and-retrieval-part-1-12fb37b4eb6b There are two main techniques used in Word2vec: Continuous Bag of Words (CBOW) and Skip-gram

An analytical approach to tracking down one of the world’s most elusive cryptids — Watching Bigfoot researchers chasing — sometimes quite literally — circumstantial evidence, noises, and half-glimpsed shadows through the forest at night certainly makes for some great TV. I love killing time with a bit of TV, and a show called “Expedition Bigfoot” has kept me entertained on many a lunch break…

Introduction: — Who said data clustering has to be a serious business? In this carefree article, we’re diving headfirst into the amusing world of clustering algorithms. Prepare for a amusing journey as we demystify the concepts, assumptions, and Python code behind data clustering. …