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This is a CNN based model which aims to automatically classify the ECG signals of a normal patient vs. a patient with AF and has been trained to achieve up to 93.33% validation accuracy.

Home Page: http://animikh.me/

License: MIT License

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ecg-atrial-fibrillation-classification-using-cnn's Introduction

TALMEEZ FUAAD

👨‍💻 Data Scientist | 📊 Machine Learning Enthusiast | 📈 Analytics Expert

Welcome to my GitHub profile! I'm passionate about leveraging data to extract meaningful insights and solve complex problems. Here you'll find a collection of my data science projects, ranging from exploratory data analysis to machine learning applications.

🔧 Technologies & Tools

  • Programming Languages: Python, SQL, C, C++
  • Data Analysis: Pandas, NumPy, Jupyter
  • Machine Learning: Scikit-learn, TensorFlow, Keras
  • Visualization: Matplotlib, Seaborn, Plotly
  • Database: SQL
  • Version Control: Git
  • Other Tools: Excel, Tableau

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