umich-eecs445-f16

Materials for EECS 445, an undergraduate Machine Learning course taught at the University of Michigan, Ann Arbor.

Name		Name	Last commit message	Last commit date
Latest commit History 166 Commits
discussion01_matrix-calculus		discussion01_matrix-calculus
discussion02_proability-mle		discussion02_proability-mle
discussion03_linear-regression-naive-bayes		discussion03_linear-regression-naive-bayes
discussion04_connecting_the_dots		discussion04_connecting_the_dots
discussion05_NB_SVM		discussion05_NB_SVM
discussion06_ensemble		discussion06_ensemble
discussion07-bayesian-networks		discussion07-bayesian-networks
discussion08-em-bayesian-clustering		discussion08-em-bayesian-clustering
discussion09-explain-away		discussion09-explain-away
handsOn_lecture00_python_tutorial		handsOn_lecture00_python_tutorial
handsOn_lecture02_linear-algebra-optimization		handsOn_lecture02_linear-algebra-optimization
handsOn_lecture03_convex-optimization-probability		handsOn_lecture03_convex-optimization-probability
handsOn_lecture04_linear-regression-part1		handsOn_lecture04_linear-regression-part1
handsOn_lecture05_linear-regression-part2		handsOn_lecture05_linear-regression-part2
handsOn_lecture06_MLE-MAP-Coding		handsOn_lecture06_MLE-MAP-Coding
handsOn_lecture08_SVM		handsOn_lecture08_SVM
handsOn_lecture09_SVM-part2		handsOn_lecture09_SVM-part2
handsOn_lecture10_bias-variance_tradeoff		handsOn_lecture10_bias-variance_tradeoff
handsOn_lecture11_info-theory-decision-trees		handsOn_lecture11_info-theory-decision-trees
handsOn_lecture12_bagging-boosting		handsOn_lecture12_bagging-boosting
handsOn_lecture13_error-measures-and-ml-advice		handsOn_lecture13_error-measures-and-ml-advice
handsOn_lecture14_unsupervised-learning-pca-clustering		handsOn_lecture14_unsupervised-learning-pca-clustering
handsOn_lecture15_exp_families_bayesian_networks		handsOn_lecture15_exp_families_bayesian_networks
handsOn_lecture16_pgms_latent_vars_cond_independence		handsOn_lecture16_pgms_latent_vars_cond_independence
handsOn_lecture17_clustering-mixtures-em		handsOn_lecture17_clustering-mixtures-em
handsOn_lecture18_gmm-hmm		handsOn_lecture18_gmm-hmm
handsOn_lecture19_baum-welch-pgm-inference		handsOn_lecture19_baum-welch-pgm-inference
handsOn_lecture20_cnn-1		handsOn_lecture20_cnn-1
lecture01_introduction		lecture01_introduction
lecture02_linear-algebra-optimization		lecture02_linear-algebra-optimization
lecture03_convex-functions-optimization		lecture03_convex-functions-optimization
lecture04_linear-regression-part1		lecture04_linear-regression-part1
lecture05_linear-regression-part2		lecture05_linear-regression-part2
lecture06_logistic_regression		lecture06_logistic_regression
lecture07_naive-bayes		lecture07_naive-bayes
lecture08_SVM		lecture08_SVM
lecture09_SVM-part2		lecture09_SVM-part2
lecture10_bias-variance-tradeoff		lecture10_bias-variance-tradeoff
lecture11_info-theory-decision-trees		lecture11_info-theory-decision-trees
lecture12_bagging-boosting		lecture12_bagging-boosting
lecture13_error-measures-and-ml-advice		lecture13_error-measures-and-ml-advice
lecture14_unsupervised-learning-pca-clustering		lecture14_unsupervised-learning-pca-clustering
lecture15_exp_families_bayesian_networks		lecture15_exp_families_bayesian_networks
lecture16_pgms_latent_vars_cond_independence		lecture16_pgms_latent_vars_cond_independence
lecture17_clustering-mixtures-em		lecture17_clustering-mixtures-em
lecture18_gmm-hmm		lecture18_gmm-hmm
lecture19_baum-welch-pgm-inference		lecture19_baum-welch-pgm-inference
lecture20_cnn-1		lecture20_cnn-1
lecture21_cnn-2		lecture21_cnn-2
misc		misc
.gitignore		.gitignore
LICENSE		LICENSE
README.md		README.md
hw5-4.py		hw5-4.py
hw5code.py		hw5code.py

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