Anidipta/Machine-Learning-Models

All Levels MACHINE LEARNING MODELS

20
/ 100
Experimental

This collection of machine learning examples helps you understand how predictive models work by solving common real-world problems. It takes various datasets – like financial transactions, customer history, or medical records – and shows you how to build models that can forecast sales, detect fraud, or predict customer churn. This is ideal for anyone learning data science, machine learning, or analytics, including students, aspiring data scientists, or business analysts looking to apply these techniques.

No commits in the last 6 months.

Use this if you are learning machine learning and need practical, hands-on examples to understand classification, regression, clustering, or image recognition.

Not ideal if you are an experienced data scientist looking for production-ready solutions, advanced research, or highly specialized algorithms.

predictive-analytics fraud-detection customer-retention healthcare-diagnostics sales-forecasting
Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 4 / 25
Maturity 16 / 25
Community 0 / 25

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7

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Language

Jupyter Notebook

License

Apache-2.0

Last pushed

Aug 20, 2024

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