navidadkhah/MachineLearning_Algorithms
This repository contains Machine Learning Algorithms such as KNN, SVM, Trees, etc.
This project offers practical examples of core machine learning algorithms for tasks like predicting outcomes, grouping similar items, and finding patterns in data. It takes your structured dataset (like a CSV or NumPy file) as input and provides visualizations and performance metrics for various models, helping you understand how well they make predictions or identify clusters. It's designed for data scientists, analysts, or students looking to learn or apply fundamental machine learning techniques.
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Use this if you are exploring how different classification, regression, or clustering algorithms like Decision Trees, SVM, KNN, or DBSCAN work on real-world datasets and want to see their performance.
Not ideal if you need a production-ready library for deploying complex machine learning solutions or require advanced, bleeding-edge algorithms not covered here.
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Jupyter Notebook
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Last pushed
Sep 15, 2024
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