# Difference between revisions of "Machine Learning"

From MIPAL

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* [https://uni-tuebingen.de/en/180804 Probabilistic Machine Learning (Summer 2020)] by Philipp Hennig @ U. Tubingen | * [https://uni-tuebingen.de/en/180804 Probabilistic Machine Learning (Summer 2020)] by Philipp Hennig @ U. Tubingen | ||

* [http://work.caltech.edu/lectures.html Learning from data (2012)] by Yaser Abu-Mostafa @ Caltech | * [http://work.caltech.edu/lectures.html Learning from data (2012)] by Yaser Abu-Mostafa @ Caltech | ||

− | * [http://cs330.stanford.edu/ Deep Multi-Task and Meta Learning (Stanford CS330, Fall 2021, Chelsea Finn) | + | * [http://cs330.stanford.edu/ Deep Multi-Task and Meta Learning] (Stanford CS330, Fall 2021, Chelsea Finn) |

## Revision as of 10:04, 17 December 2021

- Course for Machine Learning by Carl Edward Rasmussen and Zoubin Ghahramani
- Course for Machine Learning by David Sontag
- Course for Machine Learning by Milos Hauskrecht
- Advanced topics in Machine Learning by Milos Hauskrecht
- Course for Markov Random Fields by Kyomin Jung
- Tutorial on particle filtering and smoothing
- Sequential Monte Carlo Methods & Particle Filters Resources
- Deep learning tutorial page
- Video lecture on Graphical Models by Eric Xing@CMU
- An easy tutorial on active learning
- Latent Dirichlet Allocation with Variational Inference (Mean Field)
- Course on Variational Inference by David Blei@Princeton
- Various Courses (mostly on NLP) by Jordan Boyd-Graber@Maryland
- Probabilistic Machine Learning (Summer 2020) by Philipp Hennig @ U. Tubingen
- Learning from data (2012) by Yaser Abu-Mostafa @ Caltech
- Deep Multi-Task and Meta Learning (Stanford CS330, Fall 2021, Chelsea Finn)