Machine learning: Difference between revisions
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* Expectation Maximization - Brandon and Jonathan | * Expectation Maximization - Brandon and Jonathan | ||
* Hidden Markov models | * Hidden Markov models | ||
* Rate-based networks & error back-propagation learning - Scott | * [[Media:ML-ANNs.pdf | Rate-based networks & error back-propagation learning]] - Scott | ||
* Support Vector Machines - Jerry | * Support Vector Machines - Jerry | ||
* Deep belief networks | * Deep belief networks | ||
Revision as of 01:44, 17 May 2016
Our Journal Club slides about ML will be posted here.
- Machine learning introduction - Gunnar
- Linear Regression - Sisi
- Linear Classification - Parisa
- Markov Chain Montre Carlo - Gunnar
- Introduction to PCA and ICA - Cindy
- Expectation Maximization - Brandon and Jonathan
- Hidden Markov models
- Rate-based networks & error back-propagation learning - Scott
- Support Vector Machines - Jerry
- Deep belief networks
- Supervised vs. unsupervised learning
Machine learning books
- Tom Mitchell's book
- Smola & Vishwanathan's book
- Daume's book
- Murphy's book
- Shalev-Shwartz & Ben-David's book
- Nilsson's book
- Harrington's book
- Ian Goodfellow, Yoshua Bengio, and Aaron Courville's book
