The project's objective is to harness a HR Analytics dataset. With predictive proccess I tried to equip HR management with actionable insights, enabling them to proactively address attrition issues and implement targeted retention strategies.
Practice codes for Machine Learning, Data Mining and NLP in Python
Association Rule Mining Using FP-Growth & ANN Techniques
Python Implementation of data mining algorithms(Apriori, Eclact, FP Growth ).
A Data Mining project which focuses on the comparison between different un-supervised clustering algorithms on geographical data
Course Code: CS626, MCS Batch-2019 (Final Year) Evening
Market basket analysis is a technique used mostly by retailers to identify which products clients purchase together most frequently. This involves analyzing point of sale (POS) transaction data to identify the correlations between different items according to their co-occurrence in the data.
This contains all projects that I have done during my master degree.
Datamining concepts
A data mining project using the Apriori algorithm for Market Basket Analysis. Association rules were generated and interpreted across various parameter settings to discover purchasing patterns in retail transaction data.
Used clustering algorithms such as K-Means, Fuzzy C-Means, and Density-Based Algorithms like DBScan to cluster three datasets and reported result of the best algorithm after 200 random starting points.[part of my data mining course]
some training, learning and TD/TP ressources
Data Mining Model For Detection of Fraudulent Behaviour
Desarrollo de algoritmos de Data Mining para encontrar reglas de asociación
Data Mining 2 project on tabular and wearable time-series analysis using machine learning, clustering, explainable AI, motifs and shapelets.
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