Neural process family
Meta-learning a distribution over predictors using the Neural Process Family.
Blog posts
**Disclaimer:** This is very old documentation and may be significantly out of date. Content here is preserved for archival purposes and may no longer reflect current best practices or my present views.
2020
2019
Optimization
ML concepts: optimization.
Linear programming
Optimization concepts: linear programming.
Reinforcement learning
ML concepts: reinforcement learning.
Temporal difference learning
RL concepts: temporal difference learning.
Monte Carlo GPI
RL concepts: monte carlo GPI.
Dynamic programing
RL concepts: dynamic programming.
Reinforcement learning
RL concepts: basics.
Variational autoencoder
ML concepts: VAE.
2017
Decision trees
ML concepts: decision trees.
Supervised vs unsupervised
ML concepts: supervised vs unsupervised learning.
Parametric vs non parametric
ML concepts: parametric vs non parametric.
Naive Bayes
ML concepts: Naive Bayes.
Evaluation metrics
ML concepts: evaluation metrics.
No free lunch
ML concepts: no free lunch.
Information theory
ML concepts: information theory.
Generative vs discriminative
ML concepts: generative vs discriminative.
Curse of dimensionality
ML concepts: curse of dimensionality.
Resources for learning about ML
Review of resources to learn about ML.
Machine learning glossary
Machine Learning glossary with a focus on intuition