# Difference between revisions of "Machine Learning"

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(Created page with "* [http://people.cs.pitt.edu/~milos/courses/cs2750/ Course for Machine Learning] by Milos Hauskrecht * [http://people.cs.pitt.edu/~milos/courses/cs3750/ Advanced topics in Mac...") |
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+ | * [http://mlg.eng.cam.ac.uk/teaching/4f13/1314/ Course for Machine Learning] by Carl Edward Rasmussen and Zoubin Ghahramani | ||

+ | * [http://cs.nyu.edu/~dsontag/courses/ml12/ Course for Machine Learning] by David Sontag | ||

* [http://people.cs.pitt.edu/~milos/courses/cs2750/ Course for Machine Learning] by Milos Hauskrecht | * [http://people.cs.pitt.edu/~milos/courses/cs2750/ Course for Machine Learning] by Milos Hauskrecht | ||

* [http://people.cs.pitt.edu/~milos/courses/cs3750/ Advanced topics in Machine Learning] by Milos Hauskrecht | * [http://people.cs.pitt.edu/~milos/courses/cs3750/ Advanced topics in Machine Learning] by Milos Hauskrecht | ||

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* [http://www.stats.ox.ac.uk/~doucet/smc_resources.html Sequential Monte Carlo Methods & Particle Filters Resources] | * [http://www.stats.ox.ac.uk/~doucet/smc_resources.html Sequential Monte Carlo Methods & Particle Filters Resources] | ||

* [http://deeplearning.stanford.edu/wiki/index.php Deep learning tutorial page] | * [http://deeplearning.stanford.edu/wiki/index.php Deep learning tutorial page] | ||

+ | * [https://www.cs.cmu.edu/~epxing/Class/10708-14/lecture.html Video lecture on Graphical Models] by Eric Xing@CMU | ||

+ | * [https://towardsdatascience.com/active-learning-tutorial-57c3398e34d An easy tutorial on active learning] | ||

+ | * [https://medium.com/@jonathan_hui/machine-learning-latent-dirichlet-allocation-lda-1d9d148f13a4 Latent Dirichlet Allocation with Variational Inference (Mean Field)] | ||

+ | * [https://www.cs.princeton.edu/courses/archive/fall11/cos597C/ Course on Variational Inference] by David Blei@Princeton | ||

+ | * [http://users.umiacs.umd.edu/~jbg/static/courses.html Various Courses (mostly on NLP)] by Jordan Boyd-Graber@Maryland | ||

+ | * [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 | ||

+ | * [https://home.cs.colorado.edu/~jbg/teaching/CSCI_5622/ Machine Learning class] by Jordan Boyd-Graber |

## Latest revision as of 08:34, 28 April 2022

- 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
- Machine Learning class by Jordan Boyd-Graber