Data Science Algorithms

This repository contains a collection of data science algorithms implemented in Python. These algorithms cover various aspects of data science, including data preprocessing, exploratory data analysis, machine learning and more.

Introduction

Data science is a rapidly growing field that involves extracting knowledge and insights from data using various techniques and algorithms. This repository aims to provide a comprehensive collection of algorithms commonly used in data science projects. Whether you are a beginner or an experienced data scientist, this repository can serve as a valuable resource to explore, learn and apply different algorithms in your projects.

Algorithms

The repository currently includes the following algorithms:

1. Classification with K-NN
2. Regression with K-NN
3. Span filter with Naive Bayes
4. House Price Prediction with Simple Linear Regression
5. House Price Predicting with Multiple Regression

Each algorithm is implemented as a separate Python module and is accompanied by a Jupyter Notebook that demonstrates its usage on example datasets. The implementation strives for clarity, simplicity and ease of understanding, making it suitable for educational purposes as well.

Usage

To use the algorithms in this repository, follow these steps:

1. Clone the repository to your local machine:

   git clone https://github.com/hercozauzau/data_science--algorithms.git
   

2. Install the required dependencies.

3. Explore the algorithms by navigating through the repository's directory structure. Each algorithm is contained within a separate folder and accompanied by a Jupyter Notebook that provides detailed explanations and examples.

4. Open the desired Jupyter Notebook using Jupyter Notebook or JupyterLab.

5. Run the code cells in the notebook to see the algorithm in action, modify them as needed and analyze the results.

6. Feel free to experiment, adapt and extend the algorithms to suit your specific needs and datasets.

Contributing

Contributions to this repository are welcome! If you have implemented additional data science algorithms or made improvements to the existing ones, please feel free to submit a pull request. Before submitting a pull request, make sure to adhere to the repository's code style and provide appropriate documentation.

If you have any suggestions, bug reports, or feature requests, please open an issue on the repository's issue tracker.

I hope you find this repository helpful in your data science journey. Happy exploring and analyzing data with these algorithms!

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Author

• Hérco ZauZau
• Project Link: https://github.com/HercoZauZau/Data_Science--algorithms