"Frequent Mining Algorithms" is a Python library that includes frequent mining algorithms. This library contains popular algorithms used to discover frequent items and patterns in datasets. Frequent mining is widely used in various applications to uncover significant insights, such as market basket analysis, network traffic analysis, etc.
repository showcasing Machine Learning code: KNN, KMeans, Random Forest, Decision Tree, Apriori, Conflict Serializable, Naive Bayes used for skin detection and UCI dataset evaluation to check accuracy. Extensively tested on reliable datasets like breast_cancer and iris, providing valuable insights for ML training and testing.
Tableau Prep+Python:Basket Case Analysis with Superstore. Setup: People who bought product X and product Y might be interested in product Z. By analyzing a lot of transactional data we try to distill association rules to make such statements. The output table out the Tableau Prep flow can be implemented in various ways. Tools: Tableau Prep + Pyt…
CineSLEUTH is an intelligent movie recommendation system that combines advanced ML techniques such as TF-IDF vectorization, cosine similarity, fuzzy matching, and Apriori-based collaborative filtering. The system provides highly accurate and personalized movie recommendations for users.