Machine-Learning-Projects

Welcome to my repository of machine-learning projects! This repository features machine learning projects mostly focused on healthcare. Each project applies various techniques to analyze and classify medical conditions using real-world datasets, including breast cancer classification and tumor detection, showcasing the potential of machine learning to improve diagnostics and patient care.

Table of Contents

1. Projects
2. Technologies Used
3. Getting Started

Projects

1. Breast Cancer Classification

• Description: This project aims to classify breast cancer images into malignant and benign categories using convolutional neural networks (CNNs).
• Dataset: Utilizes the Breast Histopathology Images dataset available on Kaggle.
• Key Techniques: Data augmentation, transfer learning, and model evaluation using accuracy and F1 score.

2. Tumor Detection

• Description: This project focuses on detecting tumors using deep learning techniques in medical imaging.
• Dataset: MRI or CT scan images sourced from publicly available datasets.
• Key Techniques: U-Net architecture for image segmentation and evaluation metrics like IoU (Intersection over Union).

Technologies Used

• Python
• TensorFlow / Keras
• Scikit-learn
• Pandas
• NumPy
• Matplotlib / Seaborn for data visualization

Getting Started

To get started with these projects, clone the repository to your local machine:

git clone https://github.com/yourusername/machine-learning-projects.git