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Author: joelgrus

links.md

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+Links
+=====
+
+## Preface
+
+[Data Science Venn Diagram](http://drewconway.com/zia/2013/3/26/the-data-science-venn-diagram)
+
+## 1. Introduction
+
+[OkCupid Questions](http://blog.okcupid.com/index.php/the-best-questions-for-first-dates/)
+
+[Facebook on coordinated migration](https://www.facebook.com/notes/facebook-data-science/coordinated-migration/10151930946453859)
+
+[Facebook on NFL fandom](https://www.facebook.com/notes/facebook-data-science/nfl-fans-on-facebook/10151298370823859)
+
+[Target's predictive modeling](http://www.nytimes.com/2012/02/19/magazine/shopping-habits.html)
+
+[Making government more effective](http://www.marketplace.org/topics/tech/beyond-ad-clicks-using-big-data-social-good)
+
+[Helping homelessness](http://dssg.io/2014/08/20/paths-homelessness.html)
+
+[Improving public health](https://plus.google.com/communities/109572103057302114737)
+
+## 2. A Crash Course in Python
+
+http://python.org
+
+[Anaconda](https://store.continuum.io/cshop/anaconda/)
+
+[pip](https://pypi.python.org/pypi/pip)
+
+[IPython](http://ipython.org/)
+
+[the Zen of Python](http://legacy.python.org/dev/peps/pep-0020/)
+
+[official Python tutorial](https://docs.python.org/2/tutorial/)
+
+[official IPython tutorial](http://ipython.org/ipython-doc/2/interactive/tutorial.html)
+
+[IPython videos and presentations](http://ipython.org/videos.html)
+
+[Python for Data Analysis](http://shop.oreilly.com/product/0636920023784.do)
+
+## 3. Visualizing Data
+
+[matplotlib](http://matplotlib.org/)
+
+[seaborn](http://www.stanford.edu/~mwaskom/software/seaborn/)
+
+[D3.js](http://d3js.org/)
+
+[Bokeh](http://bokeh.pydata.org/)
+
+[ggplot](https://pypi.python.org/pypi/ggplot)
+
+## 4. Linear Algebra
+
+[Linear Algebra, from UC Davis](https://www.math.ucdavis.edu/~linear/)
+
+[Linear Algebra, from Saint Michael's College](http://joshua.smcvt.edu/linearalgebra/)
+
+[Linear Algebra Done Wrong](http://www.math.brown.edu/~treil/papers/LADW/LADW.html)
+
+[SciPy linear algebra module](http://docs.scipy.org/doc/scipy/reference/tutorial/linalg.html)
+
+## 5. Statistics
+
+[Non-obvious tricks for computing medians](http://en.wikipedia.org/wiki/Quickselect)
+
+[Almost "average squared deviation from the mean"](http://en.wikipedia.org/wiki/Unbiased_estimation_of_standard_deviation)
+
+["angrily accused of experimenting on your users"](http://www.nytimes.com/2014/06/30/technology/facebook-tinkers-with-users-emotions-in-news-feed-experiment-stirring-outcry.html)
+
+[SciPy stats](http://docs.scipy.org/doc/scipy/reference/stats.html)
+
+[pandas](http://pandas.pydata.org/)
+
+[StatsModels](http://statsmodels.sourceforge.net/)
+
+[OpenIntro Statistics](https://www.openintro.org/stat/textbook.php)
+
+[OpenStax Introductory Statistics](http://openstaxcollege.org/textbooks/introductory-statistics)
+
+## 6. Probability
+
+[the Monty Hall Problem](http://en.wikipedia.org/wiki/Monty_Hall_problem)
+
+[error function](http://en.wikipedia.org/wiki/Error_function)
+
+[binary search](http://en.wikipedia.org/wiki/Binary_search_algorithm)
+
+[SciPy stats](http://docs.scipy.org/doc/scipy/reference/stats.html)
+
+[Introduction to Probability](http://www.dartmouth.edu/~chance/teaching_aids/books_articles/probability_book/amsbook.mac.pdf)
+
+## 7. Hypothesis and Inference
+
+[continuity correction](http://en.wikipedia.org/wiki/Continuity_correction)
+
+[P-hacking](http://www.nature.com/news/scientific-method-statistical-errors-1.14700)
+
+["The Earth Is Round (p < .05)"](http://ist-socrates.berkeley.edu/~maccoun/PP279_Cohen1.pdf)
+
+[conjugate priors](http://www.johndcook.com/blog/conjugate_prior_diagram/)
+
+[Coursera -- Data Analysis and Statistical Inference](https://www.coursera.org/course/statistics)
+
+## 8. Gradient Descent
+
+[Active Calculus](http://gvsu.edu/s/xr/)
+
+[scikit-learn stochastic gradient descent](http://scikit-learn.org/stable/modules/sgd.html)
+
+## 9. Getting Data
+
+[running Python scripts without the Python command](http://stackoverflow.com/questions/15587877/run-a-python-script-in-terminal-without-the-python-command)
+
+[opening csv files in binary mode](http://stackoverflow.com/questions/4249185/using-python-to-append-csv-files)
+
+[BeautifulSoup](http://www.crummy.com/software/BeautifulSoup/)
+
+[requests](http://docs.python-requests.org/en/latest/)
+
+[GitHub API](http://developer.github.com/v3/)
+
+http://www.pythonapi.com/
+
+http://www.pythonforbeginners.com/development/list-of-python-apis/
+
+http://www.programmableweb.com/
+
+[Twython](https://github.com/ryanmcgrath/twython)
+
+https://apps.twitter.com/
+
+[Twitter Search API](https://dev.twitter.com/docs/api/1.1/get/search/tweets)
+
+[unicode](https://docs.python.org/2/howto/unicode.html)
+
+[Twitter Streaming API](https://dev.twitter.com/docs/api/1.1/get/statuses/sample)
+
+[scrapy](http://scrapy.org/)
+
+[pandas](http://pandas.pydata.org/)
+
+## 10. Working With Data
+
+[pandas](http://pandas.pydata.org/)
+
+[Python for Data Analysis](http://shop.oreilly.com/product/0636920023784.do)
+
+[scikit-learn matrix decomposition](http://scikit-learn.org/stable/modules/classes.html#module-sklearn.decomposition)
+
+## 11. Machine Learning
+
+[prevalence of "Luke"](http://www.babycenter.com/babyNameAllPops.htm?babyNameId=2918)
+
+[prevalence of leukemia](http://seer.cancer.gov/statfacts/html/leuks.html)
+
+[harmonic mean](http://en.wikipedia.org/wiki/Harmonic_mean)
+
+[Coursera -- Machine Learning](https://www.coursera.org/course/ml)
+
+[Caltech -- Machine Learning](https://work.caltech.edu/telecourse.html)
+
+[The Elements of Statistical Learning](http://statweb.stanford.edu/~tibs/ElemStatLearn/)
+
+## 12. Nearest Neighbors
+
+[the length represented by a degree of longitude](http://en.wikipedia.org/wiki/Longitude#Length_of_a_degree_of_longitude)
+
+[scikit-learn nearest neighbor models](http://scikit-learn.org/stable/modules/neighbors.html)
+
+## 13. Naive Bayes
+
+[SpamAssassin public corpus](https://spamassassin.apache.org/publiccorpus/)
+
+[7-Zip](http://www.7-zip.org/)
+
+[the Porter stemmer](http://tartarus.org/martin/PorterStemmer/)
+
+["A Plan for Spam"](http://www.paulgraham.com/spam.html)
+
+["Better Bayesian Filtering"](http://www.paulgraham.com/better.html)
+
+[scikit-learn Naive Bayes](http://scikit-learn.org/stable/modules/naive_bayes.html)
+
+## 14. Simple Linear Regression
+
+## 15. Multiple Regression
+
+[scikit-learn linear model](http://scikit-learn.org/stable/modules/linear_model.html)
+
+[StatsModels](http://statsmodels.sourceforge.net/)
+
+## 16. Logistic Regression
+
+[scikit-learn logistic regression](http://scikit-learn.org/stable/modules/linear_model.html#logistic-regression)
+
+[scikit-learn support vector machines](http://scikit-learn.org/stable/modules/svm.html)
+
+[libsvm](http://www.csie.ntu.edu.tw/~cjlin/libsvm/)
+
+## 17. Decision Trees
+
+[Twenty Questions](http://en.wikipedia.org/wiki/Twenty_Questions)
+
+[scikit-learn decision trees](http://scikit-learn.org/stable/modules/tree.html)
+
+[scikit-learn ensembles](http://scikit-learn.org/stable/modules/classes.html#module-sklearn.ensemble)
+
+http://en.wikipedia.org/wiki/Decision_tree_learning
+
+## 18. Neural Networks
+
+[Coursera -- Neural Networks for Machine Learning](https://www.coursera.org/course/neuralnets)
+
+[Neural Networks and Deep Learning](http://neuralnetworksanddeeplearning.com/)
+
+[pybrain](http://pybrain.org/)
+
+## 19. Clustering
+
+[RGB color model](http://en.wikipedia.org/wiki/RGB_color_model)
+
+[SciPy](http://www.scipy.org/)
+
+## 20. Natural Language Processing
+
+["What is Data Science"](http://radar.oreilly.com/2010/06/what-is-data-science.html)
+
+[Natural Language Toolkit](http://www.nltk.org/)
+
+[NLTK book](http://www.nltk.org/book/)
+
+[gensim](http://radimrehurek.com/gensim/)
+
+## 21. Network Analysis
+
+[Centrality](http://en.wikipedia.org/wiki/Centrality)
+
+[NetworkX](http://networkx.github.io/)
+
+[Gephi](http://gephi.github.io/)
+
+## 22. Recommender Systems
+
+[Crab](http://muricoca.github.io/crab/)
+
+[Graphlab recommender toolkit](http://graphlab.com/products/create/docs/graphlab.toolkits.recommender.html)
+
+[Netflix prize](http://www.netflixprize.com/)
+
+## 23. Databases
+
+[SQLite](http://www.sqlite.org/)
+
+[MySQL](http://www.mysql.com/)
+
+[PostgreSQL](http://www.postgresql.org/)
+
+[MongoDB](http://www.mongodb.org/)
+
+[NoSQL](http://en.wikipedia.org/wiki/NoSQL)
+
+## 24. Map-Reduce
+
+[Hadoop](http://hadoop.apache.org/)
+
+[Elastic MapReduce](http://aws.amazon.com/elasticmapreduce/)
+
+[mrjob](https://github.com/Yelp/mrjob)
+
+[Spark](http://spark.apache.org/)
+
+[Storm](http://storm.incubator.apache.org/)
+
+## 25. Go Forth And Do Data Science
+
+[IPython](http://ipython.org/)
+
+[NumPy](http://www.numpy.org/)
+
+[pandas](http://pandas.pydata.org/)
+
+[scikit-learn](http://scikit-learn.org/)
+
+[many, many scikit-learn examples](http://scikit-learn.org/stable/auto_examples/)
+
+[matplotlib examples](http://matplotlib.org/examples/)
+
+[matplotlib gallery](http://matplotlib.org/gallery.html)
+
+[seaborn](http://web.stanford.edu/~mwaskom/software/seaborn/)
+
+[D3.js](http://d3js.org/)
+
+[D3 gallery](https://github.com/mbostock/d3/wiki/Gallery)
+
+[Bokeh](http://bokeh.pydata.org/)
+
+[Data.gov](http://www.data.gov/)
+
+[r/datasets](http://www.reddit.com/r/datasets) and [r/data](http://www.reddit.com/r/data)
+
+[Amazon public data sets](http://aws.amazon.com/public-data-sets/)
+
+[100 Interesting Data Sets](http://rs.io/100-interesting-data-sets-for-statistics/)
+
+[Kaggle](https://www.kaggle.com/)
+
+[Hacker News](https://news.ycombinator.com/news)
+
+[Hacker News Story Classifier](https://github.com/joelgrus/hackernews)
+
+[Seattle Real-Time 911](http://www2.seattle.gov/fire/realtime911/getRecsForDatePub.asp?action=Today)
+
+[social network analysis of fire trucks](https://github.com/joelgrus/fire)
+
+[machine learning on t-shirts](https://github.com/joelgrus/shirts)