Welcome to the Machine Learning Algorithms repository! This repository contains implementations of various machine learning algorithms in Jupyter Notebook format. The implementations are based on concepts from "The Hundred-Page Machine Learning Book".
In this repository, you will find implementations of the following machine learning algorithms:
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Linear Regression
- Simple Linear Regression
- Multiple Linear Regression
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Polynomial Regression
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Logistic Regression
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Naive Bayes
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Decision Tree Classifier
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Support Vector Machine (SVM)
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K-Nearest Neighbors (KNN)
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Multi-Layer Perceptron
"The Hundred-Page Machine Learning Book" is a concise yet comprehensive resource that covers fundamental machine learning concepts in a simplified manner. The implementations in this repository aim to provide practical examples based on the concepts outlined in the book.
Each algorithm implementation is provided in a separate Jupyter Notebook file for easy exploration and understanding. You can run these notebooks in your local environment or in an online Jupyter environment for experimentation and learning.
If you have any suggestions, feature requests, or bug reports, feel free to open an issue or submit a pull request. Your contributions are highly appreciated!
This repository is licensed under the MIT License. See the LICENSE file for more details.