Probabilistic Machine Learning  Introduction
Probabilistic machine learning  foundations and frontiers
Speaker: Zoubin Ghahramani Video: https://livestream.com/oxuni/StracheylectureGhahramani/videos/151163648
My notes from the Strachey lecture on Probabilistic machine learning at Oxford University.
 Related terms
 deep learning
 data science
 neural networks
 ai
 Applications
 computer vision
 image captioning
 face detection
 speech recognition
 scientific data analysis
 recommender systems
 selfdriving cars
 robotics
 dogs playing football
 financial prediction
 computer games
 libratus: machine poker player
 computer vision
 Canonical problems
 classification: predict discrete class label from input data
 regression: predict continuous quantities from input data
 clustering: group data together
 dimensionality problem
 semisupervised learning: learn from both labelled and unlabelled data
 reinforcement learning
 Deep learning systems are like neural networks of the 80s and 90s with innovations in some areas:
 volume of data
 larger compute resources

Limitations od deep learning

Probabilistic representation of uncertainty
 Automating machine learning
References
 https://en.wikipedia.org/wiki/Bayesβ_theorem
 https://www.automaticstatistician.com/index/
 https://en.wikipedia.org/wiki/Prior_probability
 https://en.wikipedia.org/wiki/Causality