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In this case study, a decision tree is build to predict the income of a given population, which is labelled as <= 50𝐾𝑎𝑛𝑑> 50K on the basis of various attributes (predictors) like age, working class type, marital status, gender, race etc.
Python package for automated scraping, cleaning, and AI-driven classification of new drug approvals. Harness OpenAI's GPT-3.5 Turbo to transform complex data into actionable insights
Discover ROPAC, a novel rule-based classifier we proposed. Here, you'll find the code, data, and original paper detailing this groundbreaking data classification algorithm.
In this data science course, you will be given clear explanations of machine learning theory combined with practical scenarios and hands-on experience building, validating, and deploying machine learning models. You will learn how to build and derive insights from these models using Python, and Azure Notebooks.
Resiliency is an ensemble binning method that considers how frequently a geographic entity (e.g., county) falls in a particular bin across multiple comparable data binning methods. This application helps users visualize and interact with the outputs of Resiliency on a variety of datasets.