Welcome to the Machine Learning for Beginners repository! This project is designed to accompany the Machine Learning for Beginners YouTube Playlist, providing resources, code examples, and exercises to enhance your learning experience.
This repository serves as a companion to the Machine Learning for Beginners YouTube Playlist. It contains:
- Jupyter notebooks with code examples.
- Datasets used in the tutorials.
- Exercises to practice your skills.
- Additional resources for further learning.
Before you begin, ensure you have the following installed:
Familiarity with basic programming concepts is recommended.
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Clone the Repository
git clone https://github.com/duttaturja/FromZero2ML.git cd FromZero2ML -
Create a Virtual Environment
python3 -m venv venv source venv/bin/activate # On Windows, use venv\Scripts\activate
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Install Dependencies
pip install -r requirements.txt
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Usage Navigate to the desired module's directory. Open the Jupyter notebook:
jupyter notebook.ipynb
Follow along with the code examples and exercises.
The course is structured into several modules, each focusing on different aspects of Machine Learning:
- Introduction to Machine Learning
- Data Preprocessing
- Regression Algorithms
- Classification Algorithms
- Clustering Algorithms
- Dimensionality Reduction
- Model Evaluation and Validation
- Advanced Topics
Each module contains:
- A Jupyter notebook with explanations and code examples.
- A dataset for practice.
- Exercises to test your understanding.
We (Microsoft) welcome contributions! Please read our Contributing Guidelines to get started.
This project is licensed under the MIT License.
Happy learning! If you have any questions or feedback, feel free to open an issue or submit a pull request.