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README.md

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 * For more details on Naive Bayes classification, Wikipedia has two excellent articles ([Naive Bayes classifier](http://en.wikipedia.org/wiki/Naive_Bayes_classifier) and [Naive Bayes spam filtering](http://en.wikipedia.org/wiki/Naive_Bayes_spam_filtering)), and Cross Validated has a good [Q&A](http://stats.stackexchange.com/questions/21822/understanding-naive-bayes).
 * When applying Naive Bayes classification to a dataset with continuous features, it is better to use [GaussianNB](http://scikit-learn.org/stable/modules/generated/sklearn.naive_bayes.GaussianNB.html) rather than [MultinomialNB](http://scikit-learn.org/stable/modules/generated/sklearn.naive_bayes.MultinomialNB.html). This [notebook](notebooks/14_types_of_naive_bayes.ipynb) compares their performances on such a dataset. Wikipedia has a short [description](https://en.wikipedia.org/wiki/Naive_Bayes_classifier#Gaussian_naive_Bayes) of Gaussian Naive Bayes, as well as an excellent [example](https://en.wikipedia.org/wiki/Naive_Bayes_classifier#Sex_classification) of its usage.
 * These [slides](http://www.umiacs.umd.edu/~jbg/teaching/DATA_DIGGING/lecture_05.pdf) from the University of Maryland provide more mathematical details on both logistic regression and Naive Bayes, and also explain how Naive Bayes is actually a "special case" of logistic regression.
-* Andrew Ng has a [paper](https://cs.stanford.edu/people/ang//papers/nips01-discriminativegenerative.pdf) comparing the performance of logistic regression and Naive Bayes across a variety of datasets.
+* Andrew Ng has a [paper](http://ai.stanford.edu/~ang/papers/nips01-discriminativegenerative.pdf) comparing the performance of logistic regression and Naive Bayes across a variety of datasets.
 * If you enjoyed Paul Graham's article, you can read [his follow-up article](http://www.paulgraham.com/better.html) on how he improved his spam filter and this [related paper](http://www.merl.com/publications/docs/TR2004-091.pdf) about state-of-the-art spam filtering in 2004.
 * Yelp has found that Naive Bayes is more effective than Mechanical Turks at [categorizing businesses](http://engineeringblog.yelp.com/2011/02/towards-building-a-high-quality-workforce-with-mechanical-turk.html).