Customer Segmentation Using Unsupervised Machine Learning Algorithms
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Updated
Jul 10, 2023 - Jupyter Notebook
Customer Segmentation Using Unsupervised Machine Learning Algorithms
Outlier detection based on random forest models
Micro-clusters-based Outlier Explanations for Data Streams
Data Preprocessing for Machine Learning
Online Retail Market Customer Analysis of over 0.5M+ points to find the target customers based on Recency, Frequency and Total Revenue contributed by a customer using K-Means & Agglomerative Clustering.
Scripts and notes related to the manuscript: Stuart KC & Cardilini APA 2021 Signatures of selection in a recent invasion reveal adaptive divergence in a highly vagile invasive species. Molecular Ecology 30(6):1419-1434, doi.org/10.1111/mec.15601 † joint first author ‡ joint last author.
research about imbalanced learning & anomaly detection (tabular, time series)
This repo includes regression analysis on AAPL stock. Basic statistics, visualization, outlier detection and regression modeling steps are included.
Business analysis and Business prediction with Pandas on tabular data using statistics and sklearn
To identify customers who are more likely to default loan repayment
Create a model to tracking AOV.
X Education Organization wants to identify if a customer registered on their website for enquiry is a potential customer or not. Using past data to build a machine learning algorithm
Scripts and notes related to the manuscript: Stuart KC et al. 2022. Historical museum samples enable the examination of divergent and parallel evolution during invasion. Molecular Ecology, 31(1): 1836-1852, doi.org/10.1111/mec.16353
Given the details of cell nuclei taken from breast mass, objective is to predict whether or not a patient has breast cancer using the Ensembling Techniques. This is a classification problem. The dataset consists of several predictor variables and one target variable, Diagnosis. The target variable has values 'Benign' and 'Malignant', where 'Beni…
Handling Missing Values and Outliers
Vault of variety of topics taught for Rayan Contest
Credit Card Fraud Detection Using Unsupervised Outlier Analysis
Predicting the cab booking using ML algorithms by considering the various conditions of seasons, day timing, & environment
Programming assignments completed for course CSE - 5334 Data Mining under Professor Dr. Marnim Galib.
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