InData Science at MicrosoftbyKaixin WangIntroduction to clustering-based customer segmentationCustomer segmentation is a key technique used in business and marketing analysis to help companies better understand the user base and…Nov 7, 20231Nov 7, 20231
InTDS ArchivebySamuele MazzantiAre You Still Using the Elbow Method?The Elbow method is the most popular way to find the number of clusters for k-means. But there are much better alternativesFeb 3, 202313Feb 3, 202313
InTDS ArchivebySaul DobilasGMM: Gaussian Mixture Models — How to Successfully Use It to Cluster Your Data?An intuitive explanation of GMMs with helpful Python examplesMay 23, 20213May 23, 20213
InTDS ArchivebyAnas Al-MasriHow Does k-Means Clustering in Machine Learning Work?One of the most famous topics under the realm of Unsupervised Learning in Machine Learning is k-Means Clustering. Even though this…May 14, 20195May 14, 20195
InTDS ArchivebyMaarten GrootendorstCluster Analysis: Create, Visualize and Interpret Customer SegmentsExploring methods for cluster analysis, visualizing clusters through dimensionality reduction and interpreting clusters through exploring…Jul 30, 201911Jul 30, 201911
IncomunidadedsbyDjalma JuniorPrecision, Recall ou F1-Score ? Qual a melhor métrica para utilizar em seu modelo?Fala galera dos dados! vamos falar aqui sobre três métricas de classificação para serem utilizadas em seus modelos da melhor forma e…Jun 9, 2022Jun 9, 2022
Moez AliUnsupervised K-Means Clustering in PythonAn end-to-end example of training and analyzing unsupervised K-Means clustering model in Python.Jun 16, 20222Jun 16, 20222
InTDS ArchivebyTirthajyoti SarkarClustering metrics better than the elbow-methodWhat metric to use for visualizing and determining an optimal number of clusters much better than the usual practice — elbow method.Sep 6, 20199Sep 6, 20199
InGeek CulturebyAudhi AprilliantThe k-modes as Clustering Algorithm for Categorical Data TypeThe explanation of the theory and its application in real problemsJun 22, 20212Jun 22, 20212
Volodymyr HolombHow do we know that your customers are leaving?At RBC Group we defined a solution to label churn customers based purely on the frequency and the sum of their orders. Here is how it…May 19, 20221May 19, 20221
Mazen AhmedData Science Project | Clustering Mixed DataStart to Finish Clustering Analysis | Data Series | Project 3Dec 29, 20211Dec 29, 20211
InTDS ArchivebyLuca De AngelisPredicting Customer Lifetime Value with “Buy ‘Til You Die” probabilistic models in PythonWhat is a customer worth? How many more times a customer will purchase before churning? How likely is he to churn within the next 3 months…Jun 12, 201911Jun 12, 201911
InTDS ArchivebyAdam BrownellCustomer Behavior Modeling: Buy-til-you-Die ModelsA brief intro to the BTYD family, Pareto/NBD, & Pareto/GGG for Predicting Buying BehaviorJan 19, 20212Jan 19, 20212
InTDS ArchivebyDhruvil KaraniA Practical Guide on K-Means ClusteringGoing beyond the theory and getting the best out of your K-Means clustering algorithmMar 27, 20221Mar 27, 20221
InTDS ArchivebyJorge Martín LasaosaClustering on numerical and categorical features.May 29, 202113May 29, 202113
InGeek CulturebyAlexandre HenriqueStop using the Elbow MethodSilhouette Analysis: A more precise approach to finding the optimal number of clusters using K-MeansOct 31, 20215Oct 31, 20215
InTDS ArchivebySaupin GuillaumeElbow detection for clustering using splinesOptimizing the number of clusters with splinesMar 28, 2022Mar 28, 2022
