Unsupervised Feature Selection to Identify Important ICD-10 Codes for Machine Learning
The Employee Attrition Control project uses data analysis and predictive modeling to understand and address employee turnover. It provides insights and recommendations to reduce attrition and improve employee satisfaction and retention.
Spam Classifier using Naive Bayes and Other Machine Learning Algorithms. This project aims to build a spam classification system that can accurately detect whether a given message is spam or ham (not spam). The system utilizes text preprocessing techniques and multiple machine learning models to ensure high accuracy and precision.
Exploration and analysis of historical Olympic data to identify trends, such as participation growth, top-performing countries, and medal distribution over time.
Movie Recommender based on Content based filtering.
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