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Drew Conway's venn diagramhttp://drewconway.com/zia/2013/3/26/the-data-science-venn-diagram
Cheat Sheet of a Modern Data Scientisthttp://www.marketingdistillery.com/2014/08/30/data-science-skill-set-explained/
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How do I Become a Data Scientist?http://www.quora.com/How-do-I-become-a-data-scientist
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Data Science Bootcampshttp://yet-another-data-blog.blogspot.com/2014/04/data-science-bootcamp-landscape-full.html
Coursera Machine Learning Coursehttps://www.coursera.org/course/ml
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Visualizations of Data Structureshttp://www.cs.usfca.edu/~galles/visualization/Algorithms.html
Data Structures CheatSheet & Big Oh Notationhttp://bigocheatsheet.com/
Data Structures CheatSheet -smaller more readablehttps://www.clear.rice.edu/comp160/data_cheat.html
Coursera: Stanford Algorithms Design & Analysis https://class.coursera.org/algo-006
Statistics Without the Agonizing Painhttps://www.youtube.com/watch?v=5Dnw46eC-0o
Probability Programming and Bayesian Methods for Hackershttp://nbviewer.ipython.org/github/CamDavidsonPilon/Probabilistic-Programming-and-Bayesian-Methods-for-Hackers/blob/master/Prologue/Prologue.ipynb
Probabilistic Programming and Bayesian Methods for Hackershttps://github.com/CamDavidsonPilon/Probabilistic-Programming-and-Bayesian-Methods-for-Hackers
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Beautiful Soup Cheat Sheethttp://youkilljohnny.blogspot.com/2014/03/beautifulsoup-cheat-sheet-parse-html-by.html
Requestshttp://docs.python-requests.org/en/latest/
Unix for Processinghttp://www.theunixschool.com/p/awk-sed.html
Pandashttp://pandas.pydata.org/
SciKit Learn for Preprocessinghttp://scikit-learn.org/stable/modules/preprocessing.html#preprocessing
Regular Expressionshttp://www.zytrax.com/tech/web/regex.htm
SQLhttp://www.postgresql.org/
Psycopghttp://initd.org/psycopg/
SQL Cheet Sheethttp://www.sql-tutorial.net/sql-cheat-sheet.pdf
SQLZoohttp://sqlzoo.net/wiki/Main_Page
SQLSchoolhttp://sqlschool.modeanalytics.com/
MongoDBhttp://www.mongodb.org/
PyMongohttp://api.mongodb.org/python/current/tutorial.html
MongoDB - cheatsheethttps://blog.codecentric.de/files/2012/12/MongoDB-CheatSheet-v1_0.pdf
Apache Hivehttps://hive.apache.org/
Hive Cheatsheethttp://hortonworks.com/wp-content/uploads/downloads/2013/08/Hortonworks.CheatSheet.SQLtoHive.pdf
ElasticSearchhttp://www.elasticsearch.org/
Neo4jhttp://www.neo4j.org/
Redishttp://redis.io/
Redshifthttp://aws.amazon.com/redshift/
Hadoop - the definitive guidehttp://ce.sysu.edu.cn/hope/UploadFiles/Education/2011/10/201110221516245419.pdf
Sparkhttps://spark.apache.org/
MRjobhttps://github.com/Yelp/mrjob
A visual introduction to Machine Learninghttp://www.r2d3.us/visual-intro-to-machine-learning-part-1/
SciKit-Learnhttp://scikit-learn.org/stable/
NLTKhttp://www.nltk.org/
Tour of Machine Learning Algorithmshttp://machinelearningmastery.com/a-tour-of-machine-learning-algorithms/
VIDEO - How to get started w/mLhttps://www.youtube.com/watch?v=uBorfxosVYs
Some ML methods classifiedhttp://nyghtowlblog.files.wordpress.com/2014/04/ml_algorithms.png?w=535&h=311
SciKit-imagehttp://scikit-image.org/
Machine Learning CheatSheethttps://github.com/soulmachine/machine-learning-cheat-sheet
Awesome Machine Learninghttps://github.com/josephmisiti/awesome-machine-learning
MathematicalMonk ML videoshttps://www.youtube.com/playlist?list=PLD0F06AA0D2E8FFBA
Logistic Regression Explainedhttp://www.appstate.edu/~whiteheadjc/service/logit/intro.htm#hypothesis
Video explaining how Random Forests Algorithm workshttps://www.youtube.com/watch?v=o7iDkcpOr_g
Random Forest Explainedhttp://citizennet.com/blog/2012/11/10/random-forests-ensembles-and-performance-metrics/
Machine Learning 101http://www.erogol.com/large-set-machine-learning-resources-beginners-mavens/
HackerNews for Deep Learninghttp://news.startup.ml/
Deeplearning4jhttp://deeplearning4j.org/
Neural Networks Explained - Videohttps://www.youtube.com/watch?v=bxe2T-V8XRs
Deep Learning Tutorialhttp://deeplearning.net/tutorial/deeplearning.pdf
What is Deep Learninghttp://blog.shakirm.com/2015/06/a-statistical-view-of-deep-learning-vi-what-is-deep/?utm_content=bufferae750&utm_medium=social&utm_source=linkedin.com&utm_campaign=buffer
Free Online Deep Learning Bookhttp://neuralnetworksanddeeplearning.com/
The Brain vs Deep Learning - Blog Posthttps://timdettmers.wordpress.com/2015/07/27/brain-vs-deep-learning-singularity/
ANN & Computational Intelligence Forecasting Competitionhttp://www.neural-forecasting-competition.com/index.htm
Neural Networks for Time Series Slidedeckhttp://www.cs.cmu.edu/afs/cs/academic/class/15782-f06/slides/timeseries.pdf
SciKit Learn Flow Chart for Model Selectionhttp://scikit-learn.org/stable/tutorial/machine_learning_map/index.html
Evaluating ML Algorithmshttp://machinelearningmastery.com/how-to-evaluate-machine-learning-algorithms/
Cross-Validationhttp://robjhyndman.com/hyndsight/crossvalidation/
K-fold & Grid Search in Scikitlearnhttp://randomforests.wordpress.com/2014/02/02/basics-of-k-fold-cross-validation-and-gridsearchcv-in-scikit-learn/
Scikit-learn Cross Validation dochttp://scikit-learn.org/stable/modules/cross_validation.html
Cross Validation - how to select your final Kaggle Modelhttp://www.chioka.in/how-to-select-your-final-models-in-a-kaggle-competitio/
Ipython Notebook for Feature engineeringhttp://nbviewer.ipython.org/urls/raw2.github.com/yhat/DataGotham2013/master/notebooks/7%20-%20Feature%20Engineering.ipynb?create=1
CS Princeton Coursehttp://www.cs.princeton.edu/courses/archive/spring10/cos424/slides/18-feat.pdf
Blog Post about Feature Engineering / Data Explorationhttp://deblivingdata.net/machine-learning-tricks/
https://patch-diff.githubusercontent.com/RakesDataScience/DataScienceResources#additional-tools-or-processes
A/B Testinghttp://conversionxl.com/how-to-build-a-strong-ab-testing-plan-that-gets-results/#.
A/B Testinghttp://unbounce.com/a-b-testing/5-ways-youre-screwing-up-your-a-b-testing/
Bloom Filtershttp://nbviewer.ipython.org/github/ctb/2013-pycon-awesome-big-data-algorithms/blob/master/04-bloom-filters.ipynb
Bloom filtershttp://billmill.org/bloomfilter-tutorial/
Reservoir Samplinghttp://blog.cloudera.com/blog/2013/04/hadoop-stratified-randosampling-algorithm/
Reservoir Sampling Againhttp://www.geeksforgeeks.org/reservoir-sampling/
Monte Carlo for the Monty Hall Problemhttp://slantedwindows.com/monty-hall-meet-mr-monte-carlo/
Markov Chain Monte Carlohttp://nbviewer.ipython.org/github/CamDavidsonPilon/Probabilistic-Programming-and-Bayesian-Methods-for-Hackers/blob/master/Chapter3_MCMC/IntroMCMC.ipynb
Multithreading and Queueshttp://pymotw.com/2/Queue/
Basics of Multithreading and queseshttp://www.troyfawkes.com/learn-python-multithreading-queues-basics/
Multithreading & Queuinghttp://www.shanelynn.ie/using-python-threading-for-multiple-results-queue/
Building a Recommender Systemhttp://www.quora.com/How-can-I-start-building-a-recommendation-engine
https://patch-diff.githubusercontent.com/RakesDataScience/DataScienceResources#data-visualization
ggplothttp://ggplot.yhathq.com/
matplotlibhttp://matplotlib.org/
d3http://d3js.org/
bokehhttp://bokeh.pydata.org/
d3pyhttps://github.com/mikedewar/d3py
vincenthttp://vincent.readthedocs.org/en/latest/
seabornhttp://web.stanford.edu/~mwaskom/software/seaborn/
Scott Murray's D3 Tutorialshttps://patch-diff.githubusercontent.com/RakesDataScience/DataScienceResources/blob/master/alignedleft.com/tutorials/d3
tributary.iohttp://tributary.io
plot.lyhttp://plot.ly
blockspringhttp://blockspring.com
dot.appendhttp://enjalot.github.io/dot-append/
https://patch-diff.githubusercontent.com/RakesDataScience/DataScienceResources#design-theory
Slidedeck on Data Storytelling & Visualization http://higherlogicdownload.s3.amazonaws.com/AMSTAT/62ac7e8c-c7ec-4e98-b58b-dd540bf9e0d9/UploadedImages/dvc2014/Veena%20MendirattaASA%20Storytelling%20with%20Data%20Visualization.pdf
Accelerating Understanding Through Data Visualizationhttp://www.accenture.com/SiteCollectionDocuments/PDF/Accenture-Accellerating-Understanding-Through-Data-Visualization.pdf
https://patch-diff.githubusercontent.com/RakesDataScience/DataScienceResources#ipython-notebook-tutorials
Pandas Tutorialhttp://nbviewer.ipython.org/github/twiecki/financial-analysis-python-tutorial/blob/master/1.%20Pandas%20Basics.ipynb
Pandas / Stats Tutorialhttps://github.com/fonnesbeck/pytenn2014_tutorial
Scipy Tutorialhttp://nbviewer.ipython.org/github/jrjohansson/scientific-python-lectures/blob/master/Lecture-3-Scipy.ipynb
Numpy Tutorialhttp://nbviewer.ipython.org/github/jrjohansson/scientific-python-lectures/blob/master/Lecture-2-Numpy.ipynb
Multiple Regressions using Statsmodelshttp://nbviewer.ipython.org/urls/s3.amazonaws.com/datarobotblog/notebooks/multiple_regression_in_python.ipynb
Intro to PyMChttp://nbviewer.ipython.org/github/fonnesbeck/Bios366/blob/master/notebooks/Section4_3-Introduction-to-PyMC.ipynb
More on PyMChttp://nbviewer.ipython.org/github/CamDavidsonPilon/Probabilistic-Programming-and-Bayesian-Methods-for-Hackers/blob/master/Chapter2_MorePyMC/MorePyMC.ipynb
Kaggle Titanic Comp Tutorialhttp://nbviewer.ipython.org/github/agconti/kaggle-titanic/blob/master/Titanic.ipynb
Psycopg2 tutorial in Pythonhttps://wiki.postgresql.org/wiki/Psycopg2_Tutorial
SQL in iPythonhttp://nbviewer.ipython.org/gist/catherinedevlin/6588378
Mongo in Pythonhttp://api.mongodb.org/python/current/tutorial.html
Beautiful Soup Tutorialhttp://nbviewer.ipython.org/github/kcranston/2013-08-ku/blob/master/beautifulsoup/notebooks/00-BeautifulSoup.ipynb
Sci-Kit Learn Basicshttp://nbviewer.ipython.org/urls/raw2.github.com/yhat/DataGotham2013/master/notebooks/4%20-%20scikit-learn%20basics.ipynb?create=1
MatPlotLibhttp://nbviewer.ipython.org/github/jrjohansson/scientific-python-lectures/blob/master/Lecture-4-Matplotlib.ipynb
Choosing the right priors - Bayesianhttp://nbviewer.ipython.org/github/CamDavidsonPilon/Probabilistic-Programming-and-Bayesian-Methods-for-Hackers/blob/master/Chapter6_Priorities/Priors.ipynb
Some Basic Data Analysis in Pythonhttp://nbviewer.ipython.org/github/jvns/talks/blob/master/pyconca2013/pistes-cyclables.ipynb
Crash Course in Python for Scientistshttp://nbviewer.ipython.org/gist/rpmuller/5920182
Regular Expressionshttp://nbviewer.ipython.org/gist/rjweiss/7577022
MapReducehttp://nbviewer.ipython.org/github/cs109/content/blob/master/labs/lab8/lab8_mapreduce.ipynb
Recursionhttp://nbviewer.ipython.org/github/gumption/Motivating_and_Visualizing_Recursion_in_Python/blob/master/Motivating_and_Visualizing_Recursion_in_Python.ipynb
Recursionhttp://anandology.com/python-practice-book/functional-programming.html
Hash Table, Bloom Filter, HyperLogLoghttp://nbviewer.ipython.org/github/mlaprise/pydata2013-pds-talk/blob/master/pydata2013.ipynb
Hash tables, Binary Treeshttp://nbviewer.ipython.org/github/iit-cs429/main/blob/master/lectures/lec04/Dictionaries.ipy
Time Series- Arima & Armahttp://nbviewer.ipython.org/github/qwu-hab/geogg121/blob/master/tsa_temp.ipynb
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Data.Govhttps://www.data.gov/
California Water Resourceshttp://www.water.ca.gov/data_home.cfm
Data for Cool DS projectshttp://101.datascience.community/2014/10/17/data-sources-for-cool-data-science-projects-part-1-guest-post/
Academic Torrentshttp://academictorrents.com/
Data Basinhttp://databasin.org/
Open Energy Data Initiativehttp://en.openei.org/wiki/Main_Page
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London Data Storehttp://data.london.gov.uk/
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Analytics for Product Managershttp://www.mindtheproduct.com/2013/02/everything-a-product-manager-needs-to-know-about-analytics/
Startups, you are doing data science wrong!https://gigaom.com/2013/09/28/notice-to-startups-you-are-doing-data-science-wrong/
Product Psychologyhttp://www.productpsychology.com/category/user-behavior/
Understanding Cohort Analysishttp://amarnath14.tumblr.com/post/69790103060/understanding-cohort-analysis
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Engineering Practices in Data Sciencehttp://blog.kaggle.com/2012/10/04/engineering-practices-in-data-science/
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Kind's of Data Scientisthttp://radar.oreilly.com/2013/06/theres-more-than-one-kind-of-data-scientist.html
Data Science For Startupshttp://tomtunguz.com/data-science-types/
Building Data Science Teamshttp://radar.oreilly.com/2011/09/building-data-science-teams.html
Data Science Team Building - The Power of Collaborative Analyticshttp://www.experfy.com/blog/data-science-team-building-power-collaborative-analytics/
https://patch-diff.githubusercontent.com/RakesDataScience/DataScienceResources#data-science-applicationsuse-cases
Kaggle Data Science Use Caseshttps://www.kaggle.com/wiki/DataScienceUseCases
Data Science for each Industryhttp://www.mastersindatascience.org/industry/
Big Data Analytics News - use Caseshttp://bigdataanalyticsnews.com/big-data-use-cases/
https://patch-diff.githubusercontent.com/RakesDataScience/DataScienceResources#data-science-websitesbooks
Data Science Handbookhttps://medium.com/@pericarus/introducing-the-data-science-handbook-b2bfa216bf4b
CrossValidatedhttp://stats.stackexchange.com/
StackOverflowhttps://patch-diff.githubusercontent.com/RakesDataScience/DataScienceResources/blob/master/stackoverflow.com
Kagglehttp://www.kaggle.com
O'Reilly Mediahttp://shop.oreilly.com/category/get/data-science-kit.do
Quorahttp://www.quora.com/
Data Science @ StackExchangehttp://datascience.stackexchange.com/
https://patch-diff.githubusercontent.com/RakesDataScience/DataScienceResources#data-science-meetups-in-the-bay-area
SF Data Sciencehttp://www.meetup.com/SF-Data-Science/
Data Science for Sustainabilityhttp://www.meetup.com/Data-Science-for-Sustainability/
Python Meetup Grouphttp://www.meetup.com/sfpython/
USF Seminar Series in Analyticshttp://www.meetup.com/USF-Seminar-Series-in-Analytics/http://www.meetup.com/USF-Seminar-Series-in-Analytics/http://www.meetup.com/USF-Seminar-Series-in-Analytics/http://www.meetup.com/USF-Seminar-Series-in-Analytics/
DataKindSFhttp://www.meetup.com/DataKind-SF-Bay-Area/
SF Bayarea Machine Learninghttp://www.meetup.com/SF-Bayarea-Machine-Learning/
AirBnB Tech Talkshttp://nerds.airbnb.com/tech-talks/
https://patch-diff.githubusercontent.com/RakesDataScience/DataScienceResources#data-science-blogs
Data Stories @ Quroahttp://datastories.quora.com/
FastMLhttp://fastml.com/
FiveThirtyEight Bloghttp://fivethirtyeight.com/
Data Science Hanbookhttp://www.datasciencehandbook.me/
Simply Statistics Bloghttp://simplystatistics.org/
All The Things Techhttp://nyghtowl.io/
Musings in Data Sciencehttp://deblivingdata.net/
Zipfian Data Science Bloghttp://www.zipfianacademy.com/blog/
Machine Learning Masteryhttp://machinelearningmastery.com/
DataTauhttp://datatau.com
HackerNewshttps://news.ycombinator.com/
Quorahttp://quora.com
ThreeStoryBloghttp://blog.threestory.com/
https://patch-diff.githubusercontent.com/RakesDataScience/DataScienceResources#data-science-conferences
Stratahttp://strataconf.com/
GraphLabhttp://graphlab.com/events/conference14.html
PyDatahttp://pydata.org
https://patch-diff.githubusercontent.com/RakesDataScience/DataScienceResources#data-science-presentations
Strata Collection of Presentationshttp://strataconf.com/strata2014/public/schedule/proceedings
KDD Keynoteshttp://videolectures.net/kdd2014_newyork/
All of PyData Conference Talkshttps://github.com/DataTau/datascience-anthology-pydata
https://patch-diff.githubusercontent.com/RakesDataScience/DataScienceResources#relevant-business-processes
Lean Startuphttp://theleanstartup.com/principles
Agile Developmenthttp://en.wikipedia.org/wiki/Agile_software_development
Scrumhttp://en.wikipedia.org/wiki/Scrum_(software_development)
https://patch-diff.githubusercontent.com/RakesDataScience/DataScienceResources#start-up-resources
How to Start a Start-uphttp://startupclass.samaltman.com/
https://patch-diff.githubusercontent.com/RakesDataScience/DataScienceResources#other-open-source-data-science-content
Open Data Science Mastershttp://datasciencemasters.org/
A Practical Intro to Data Sciencehttp://www.zipfianacademy.com/blog/post/46864003608/a-practical-intro-to-data-science
LearnDataSciencehttps://github.com/nborwankar/LearnDataScience
FreeDataScienceBookshttps://github.com/chaconnewu/free-data-science-books/blob/master/free-data-science-books.md
Gallery of Ipython Notebookshttps://github.com/ipython/ipython/wiki/A-gallery-of-interesting-IPython-Notebooks
Data Science 45 Min Introshttps://github.com/DrSkippy/Data-Science-45min-Intros
Awesome Data Sciencehttps://github.com/okulbilisim/awesome-datascience
Awesome Big Datahttps://github.com/onurakpolat/awesome-bigdata
Mining the Social Webhttps://github.com/ptwobrussell/Mining-the-Social-Web-2nd-Edition
Harvard CS109 Github Repohttps://github.com/cs109/
Pete Warden's Data Science Toolkithttps://github.com/petewarden/dstk
Course Materials for Data Science Specializationhttps://github.com/DataScienceSpecialization/courses
iPython Cookbook Materialshttps://github.com/ipython-books/cookbook-code
https://patch-diff.githubusercontent.com/RakesDataScience/DataScienceResources#auxiliary-content--apps
Markablehttp://markable.in/editor/
Markdown Cheatsheethttps://github.com/adam-p/markdown-here/wiki/Markdown-Cheatsheet
LightPaperhttp://www.ashokgelal.com/lightpaper-for-mac/
iterm2http://iterm2.com/
Oh My Zshhttp://ohmyz.sh/
Sublime Text Editorhttp://www.sublimetext.com/
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