• Graduate Program
    • Why study Business Data Science?
    • Program outline
    • Courses
    • Course registration
    • Admissions
    • Facilities
      • Student Offices
      • Location
      • Housing
      • Student Council
  • Research
  • News
  • Events
    • Events Calendar
    • Events archive
    • Summer School
      • Deep Learning
      • Econometrics and Data Science Methods for Business and Economics and Finance
      • Foundations of Data Analysis and Machine Learning in Python
      • Introduction to Genome-Wide Data Analysis
      • Tinbergen Institute Summer School Program
  • Summer School
  • Alumni
Home | Events Archive | Deep Learning
Summer School

Deep Learning


  • Speaker
    Eran Raviv
  • Location
    Online
  • Date

    August 17, 2020 until August 21, 2020

Deep learning course covers theoretical and practical aspects, state-of-the-art deep learning architectures, and application examples.

Topics covered:
1. Introduction to Deep Learning (High-level definitions of fundamental concepts and first examples)
2. Deep Learning components (gradient descent models, loss functions, avoiding over-fitting, introducing asymmetry)
3. Feed forward neural networks
4. Convolutional neural networks
5. Embeddings (pre-trained embeddings, examples of pre-trained models, e.g., GloVe embeddings, Word2Vec)
6. Recurrent neural networks
7. Long-short term memory units
8. Advanced architectures (Densely connected networks, Adaptive structural learning)