文件名称:MIT-machine-learning-course
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《将UIQ应用移植到Series60 Platform》-" The UIQ applications to Series60 Platform"
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下载文件列表
| 文件名 | 大小 | 更新时间 |
|---|---|---|
| MIT machine learning course | ||
| ...........................\Introduction.pdf | ||
| ...........................\lagrange.pdf | ||
| ...........................\lecture1- Introduction.pdf | ||
| ...........................\lecture10-Boosting | complexity.pdf | |
| ...........................\lecture11-Structural risk minimization | description length.pdf | |
| ...........................\lecture12-Mixture models | EM.pdf | |
| ...........................\lecture13-EM | regularization | conditional mixtures.pdf |
| ...........................\lecture14-Non-parametric density estimation | clustering.pdf | |
| ...........................\lecture15- Clustering | Markov models.pdf | |
| ...........................\lecture16-Markov and hidden Markov models.pdf | ||
| ...........................\lecture17-Hidden Markov models.pdf | ||
| ...........................\lecture18-Viterbi | graphical models.pdf | |
| ...........................\lecture19-Bayesian networks.pdf | ||
| ...........................\lecture2-Linear regression.pdf | ||
| ...........................\lecture20-Medical diagnosis example | influence diagrams.pdf | |
| ...........................\lecture21-Influence diagrams | exact inference.pdf | |
| ...........................\lecture22-Belief propagation.pdf | ||
| ...........................\lecture23-Learning graphical models (guest lecture).pdf | ||
| ...........................\lecture3- Additive models | maximum likelihood.pdf | |
| ...........................\lecture3-Additive models | maximum likelihood.pdf | |
| ...........................\lecture4-Active learning.pdf | ||
| ...........................\lecture5-Classification.pdf | ||
| ...........................\lecture6- Logistic regression | regularization.pdf | |
| ...........................\lecture7-Regularization | Support vector machines.pdf | |
| ...........................\lecture8-Support vector machines | text classification.pdf | |
| ...........................\lecture9-Feature selection | combination of methods.pdf | |
| ...........................\Linear regression.pdf | ||
| ...........................\regularization.pdf |