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Machine-Learning-Problems

Introduction

Welcome to the Machine Learning Problem Repository! This repository serves as a collection of machine learning problems and solutions that I have encountered during my journey through the "Machine Learning Specialisation: Supervised Machine Learning" course by Andrew Ng.

The field of machine learning is rapidly evolving, and as aspiring data scientists, it is essential for us to practice and hone our skills by solving various real-world problems. This repository aims to provide a comprehensive collection of curated machine learning problems along with their corresponding solutions, showcasing the application of supervised learning algorithms covered in the course.

This repository offers a valuable resource to explore and learn from. Each problem comes with a detailed description, dataset, and a Jupyter notebook containing the implementation of the solution using popular machine learning libraries such as scikit-learn, numpy and matplotlib. By sharing my work in this repository, I hope to not only demonstrate my proficiency in applying supervised learning algorithms but also provide a valuable resource for others who are interested in exploring and learning from practical machine learning problems.

Feel free to explore the repository, experiment with the code, and use it as a reference for your own machine learning projects. Contributions and suggestions are always welcome, as I believe in fostering a collaborative and learning-focused community.

Happy-Learning!

Getting Started

To get started, clone this repository to your local machine using the following command:

git clone https://github.com/your-username/machine-learning-problem-repo.git

Feel free to explore the problem folders, run the Jupyter Notebook files, and experiment with the code. Additionally, you can contribute to this repository by adding your own solutions or suggesting improvements.

Contact

If you have any questions or suggestions regarding this repository, please feel free to contact me.

About

Here, you can find the ML problems and solutions I encountered while studying Machine Learning.

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