System for Personalized Google Scholar Alerts Processing and Data Management, and provision of ML based clustering analysis
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Updated
Jun 19, 2024 - Python
System for Personalized Google Scholar Alerts Processing and Data Management, and provision of ML based clustering analysis
Project focuses on customer segmentation using the marketing_campaign.csv dataset. The objective is to identify distinct customer groups through clustering techniques, aiding in personalized marketing strategies.
Clustering with Agglomerative and DBSCAN algorithm Machine Learning
A container load assignment problem - Heuristic Approach
This repository is a collection of programs implemented as part of Machine Learning Laboratory course at JSS Science And Technology University(SJCE).
Agglomerative Clustering from scratch without using built-in library with different hyper-parameters using Python and evaluated the cluster quality using intrinsic and extrinsic scores
Given a dataset with information about 167 countries, the goal of this experiment is to segmentate the countries in clusters to then determine which groups may need help more urgently using clustering techniques.
CIA Country Analysis and Clustering
Content: Unsupervised ML, Agglomerative & Divisive Hierarchical clustering, EDA using Dendrogram, Customer clustering
207 Machine Learning Project using various clustering models
This repository implements customer segmentation techniques to analyze credit card user behavior and identify distinct customer groups. By leveraging Python libraries like pandas, Scipy and scikit-learn.
Year 1 Data Science (HVE) course assignment (2022): cluster the data, make a dashboard with some exploratory plots
Python implementation of Agglomerative Clustering algorithm for unsupervised learning. Hierarchical clustering method that merges similar clusters iteratively. Suitable for various data types and shapes, offering insights into hierarchical structures within datasets.
In this project, unsupervised learning methods, particularly clustering, are employed to determine the optimal algorithm for predicting whether a company has achieved net profit or incurred a net loss.
Welcome to my Classical Learning Projects repository, where I showcase my work in the fields of supervised and unsupervised learning. Here, you'll find code and datasets for various projects, such as classification and clustering tasks, implemented using popular algorithms like decision trees, neural networks, and k-means.
Comparing k-means clustering with Agglomerative clustering on online shoppers intention dataset
Data preprocessing and ml clustering algorithms implementation
🤖 Machine Learning (Hierarchical Clustering) for Blobs and Cars dataset
Mall Customer Segmentation Data
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