The autoencoder_seizure_eeg_generation from i1idan

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An unofficial implementation of the paper "A comprehensive comparison of handcrafted features and convolutionalautoencoders for epileptic seizures detection in EEG signals"

License: MIT License

Jupyter Notebook 100.00%

autoencoder_seizure_eeg_generation's Introduction

class i1idan:
    """
    Hey there i'm Maryam !,
 
    """
    def __init__(self):
        self.username = 'i1idan'
        self.name = 'Maryam Saeedi '
        self.email = '[email protected]'
        self.scholar = 'https://scholar.google.com/citations?user=M7RO3xAAAAAJ&hll=en'
        self.kaggle = 'https://www.kaggle.com/i1idan'
        self.interests = ['Artificial Intelligence', 'Computer Vision',
                          'Signal Processing', 'Cognitive Sciences']
        self.skills = {
            'ai': ['TensorFlow', 'Keras', 
                    'Autokeras', 'Sklearn', 'LightGBM',
                    'CatBoost', 'XGBoost',
                    'Matlab', 'cuDNN'],
            'vision': ['OpenCV'],
            'data': ['Numpy', 'Scipy', 'Pandas', 'Matplotlib', 'Seaborn'],
            'frontend': ['HTML', 'CSS', 'JS'],
            'backend': ['Flask', 'Django', 'FastAPI']
            'database': ['MySQL', 'SQLite3', 'Redis'],
            'devops': ['ngrok', 'Docker', 'Nginx'],
            'tools': ['git', 'Jupyter notebook'],
            'misc': ['bash', 'GNU/Linux', 'ARM'],
        }