Machine Learning Coding Tutorial

Welcome to the Machine Learning Coding Tutorial repository! This project is designed to provide an easy-to-follow introduction to machine learning concepts using Python. You'll find resources, datasets, and Jupyter notebooks to help you understand and apply basic machine learning techniques.

📁 Repository Contents

• diabetes.csv: The dataset used for this tutorial, containing data related to diabetes (sourced from public datasets). You will use this data to perform various machine learning tasks, from preprocessing to building predictive models.

• ML_Coding_Session_1.ipynb: A Jupyter notebook containing code for:

  • Data Loading
  • Data Pre-processing
  • Feature Engineering
  • Exploratory Data Analysis (EDA) using Pandas, Matplotlib, and Seaborn

More tutorials will be added as the project progresses!

🚀 Getting Started

1. Clone the Repository

git clone https://github.com/muhammadrafsan/Machine-Learning-Coding-Tutorial.git

2. Navigate to the Directory

cd Machine-Learning-Coding-Tutorial

3. Install Required Packages

pip install -r requirements.txt

📚 Resources

Here are some useful resources to supplement your learning:

• Pandas
• Matplotlib
• Seaborn
• Scikit-learn

📧 Contact

If you have any questions, feel free to reach out via email at muhammad.kabir@northsouth.edu.