MachineLearning

A collection of Jupyter notebooks for learning Machine Learning, from data preprocessing to supervised learning techniques.

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Structure

notebooks/machine-learning/
│
├── pre-modeling/
│   └── data_preprocessing_and_feature_engineering.ipynb
│
└── supervised-learning/
    ├── ensemble_learning.ipynb
    ├── model_assessment.ipynb
    └── support_vector_machines.ipynb

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Contents

• Pre-modeling: Data preprocessing & feature engineering.

• Supervised Learning:

  • Ensemble methods
  • Model assessment & evaluation
  • Support Vector Machines

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Usage

1. Clone the repo:

   git clone https://github.com/your-username/MachineLearning.git

2. Install dependencies:

   pip install numpy pandas scikit-learn matplotlib seaborn jupyter

3. Run notebooks with:

   jupyter notebook

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Goal

Learn and practice core ML concepts with clear, hands-on examples.