MLSS-Indo 2020

Lectures

  1. Machine Learning Basics by Daniel Worrall (University of Amsterdam)

  2. Deep Learning Fundamental by Daniel Worrall (University of Amsterdam)

  3. Advanced Topics in Equivariance by Daniel Worrall (University of Amsterdam)

  4. Bayesian Machine Learning (Part 1) by Shakir Mohamed (Deep Mind)

  5. Information Theoretic Objectives and Robust Generalization (Part 1) by Ian Fischer (Google AI)

  6. Computational Morphology by Mustafa Mat Derris (UTHM Malaysia) and M. Arif Bijaksana (Telkom University and INACL)

  7. Bayesian Machine Learning (Part 2) by Shakir Mohamed (Deep Mind)

  8. Reinforcement Learning by Feryal Behbahani (Deep Mind) and Matthew W. Hoffman (Deep Mind)

  9. Information Theoretic Objectives and Robust Generalization (Part 2) by Ian Fischer (Google AI)

  10. Meet the speaker (Ian Fischer)

  11. Probabilistic Generative Models, VAEs and Flows by Max Welling (University of Amsterdam)

  12. Deep Learning for NLP by Katharina Kann (University of Colorado)

  13. How to write a good paper by Muhammad Haris (Bukalapak) and Adhiguna Kuncoro (Deepmind & University of Oxford)

  14. Graph Neural Nets by Max Welling (University of Amsterdam)

  15. Meet The Speaker (Shakir Mohamed)

  16. Transfer Learning for NLP by Katharina Kann (University of Colorado)

  17. Multi-lingual NLP by Adhiguna (Deepmind & University of Oxford)

  18. Super-resolution and its Application to Computer Vision Task by Muhammad Haris (Bukalapak)

Labs

  1. Machine Learning Fundamental, TensorFlow by Anditya Arifianto (Telkom University)

  2. Convolutional Neural Network by Vincent Tatan

  3. Object Detection by Rony Kalfarisi (Bukalapak)

  4. Reinforcement Learning by Feryal Behbahani (Deep Mind) and Matthew W. Hoffman (Deep Mind)

  5. Variational Auto Encoder + GAN by Anditya Arifianto (Telkom University)

  6. Deep Learning for NLP by Genta Indra Winata (The Hong Kong University of Science and Technology)

  7. LSTM, Attention Mechanism, Transformer by Genta Indra Winata (The Hong Kong University of Science and Technology)

  8. Transfer Learning for NLP by Radityo Eko Prasojo (Kata.ai)