humayuntanwar/100-days-of-Machine-Learning
A Repository for Machine Learning Algorithms for easy Understanding
This project offers a collection of practical machine learning code examples to help you understand common algorithms. It takes various datasets, such as stock prices, breast cancer diagnostics, or Titanic passenger information, and demonstrates how to apply techniques like linear regression for forecasting, K-Nearest Neighbors for classification, or K-Means for grouping data. This resource is designed for anyone, including students or data enthusiasts, who wants to see machine learning concepts in action to better grasp their real-world application.
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Use this if you are learning machine learning and want to see how fundamental algorithms are implemented and applied to different types of data.
Not ideal if you are a professional developer looking for a production-ready library or a highly optimized solution for complex, large-scale problems.
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Dec 10, 2018
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