Prediction of COVID Infection using reported symptoms

  [ Notebook (DIY) ] [ Notebook (Soln.) ]

Based on: Zoabi et al. "Machine learning-based prediction of COVID-19 diagnosis based on symptoms." npj digital medicine 4.1 (2021): 1-5.
Task: Predict COVID-19 infection from reported symptoms
Dataset: English translation of COVID infections reported by Israeli Ministry of Health
Learning objectives:
  • Explore a realistic dataset and prepare it for building a practical machine learning system
  • Think through various practical issues related to deploying such a system (e.g., class imbalance, data collection bias)
  • Build and train such an ML system addressing the issues discovered above


Attention is all you need


Paper: Vaswani, Ashish, et al. "Attention is all you need." NeurIPS 2017.
Task: Neural Machine Translation (e.g, German-English)
Dataset: Multi30k
Libraries: PyTorch, NLTK, Spacy, torchtext

Learning objectives:
  • Build a transformer model for neural machine translation
  • Train the model using proposed label smoothing loss and learning rate scheduler
  • Use the trained model to infer likely translations using
    • Greedy Decoding
    • Beam Search


  • Deep Autoencoders and Variational Autoencoders
    [Topics] [Practical]
    Noise Reduction in Machine Learning
    [Topics] [Practical]
    Advanced Convolutional Neural Network Architectures (2012 - 2018)
    [Topics] [Practical]