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PDEng Tutorial "On Deep Learning"

Tutorial "On Deep Learning" https://github.com/jpcpereira/pdeng_tutorial_deep_learning

This is a tutorial I prepared for my colleagues in the PDEng program Data Science at Jheronimus Academy of Data Science. I divided it in three sessions:

  • Part 1: Introduction to neural networks for machine learning. ()
  • Part 2: Advanced model architectures (Convolutional Neural Networks and Recurrent Neural Networks).
  • Practical coding session focusing on three applications of the architectures covered: fraud detection (anomaly detection), times series forecasting (regression), and time series classification (classification).

Materials

Part 1 and 2 slides are merged in the .pdf file "On_Deep_Learning". Pratical sessions slides are in the file "On_Deep_Learning_Practical" and code are the three Jupyter Notebooks in the repository: fraud_detection.ipynb, time_series_classification.ipynb, and time_series_forecasting.ipynb.

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