Implementing Clustering Algorithms from scratch in MATLAB and Python
En este proyecto de GitHhub podrás encontrar parte del material que utilizo para impartir las clases de Introducción a la Ciencia de Datos (Data Science) con Python.
Implementation of Decision Tree Classifier, Esemble Learning, Association Rule Mining and Clustering models(Kmodes & Kprototypes) for Customer attrition analysis of telecommunication company to identify the cause and conditions of the churn.
A Python package for unsupervised mixed datatypes clustering
Customer segmentation is the practice of dividing a customer base into groups of individuals that are similar in specific ways. You can provide different value propositions to different customer groups. Customer segments are usually determined on similarities, such as personal characteristics, preferences or behaviours that should correlate with…
Installation and implementation guidelines of ICOT, a Julia-based interpretable clustering algorithm.
Creation an Information Retrieval Service with ElasticSearch
The PyTorch implementation of the additional temporal modeling on the DeepEmoCluster framework
Segmentation des clients d'un site e-commerce (OpenClassrooms | Data Scientist | Projet 5)
Data Modelling on 2018 US midterm Election Data and US Demographic Data. Creating regression, classification and clustering models.
Technical Analysis (TA) investigation with Python. Moving averages included as well as outlier detection using signal processing and smoothing. Included as well is market characteristic detection with hurst exponent analysis.
Regression, classification, clustering and recommender systems models.
Clustering methods implementations in C++: Lloyd, K-Means, K-Means++, PAM
How does user aggregate purchasing history and hotel prices affect number of nights stay at hotel over the weekend? Interested in the relationship between hotel price and search criteria of customers.
This repository contains a variety of algorithms designed for graph clustering problems.
Testing among various Machine Learning models and parameters, in order to further study their behaviour for Classification, Regression and Clustering analysis.
the DeepMI curriculum metric is for SER tasks, which extracted by a pretrained semi-supervised DeepEmoCluster model
Repository to work on clustering exercises using machine learning
A curated repository of machine learning projects performing predictions, time-series forecasting.
House Price Prediction, Heart Disease Detection and Customer Segmentation with Python
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