A bag of tweets / February 2013

2013-02-24

Here is the latest bag of tweets*, which covers February 2013.

(*) These are interesting news that I found on Twitter and that I archive periodically.

  • TWiecki: Machine Learning in Health Care http://t.co/OW5Q6SAUhL (24 Feb)
  • dartdog: A survey of front end CSS frameworks... http://t.co/C9a79hNv1b (23 Feb)
  • zentree: Better Google Fonts, presented as 167 font families. http://t.co/K15KGdVmor (23 Feb)
  • dartdog: Pyspread http://t.co/YuSWtl4Jvr could be very interesting to both Ipython and Pandas I think... (23 Feb)
  • hmCuesta: The intersection of Data Science and Statistics http://t.co/UbEg1tblTa via @harvardstat221 (23 Feb)
  • freakonometrics: "Statistics Done Wrong" http://t.co/iAiEa1SSrV via @msgbi (23 Feb)
  • kadavy: A font that will keep your wireframes free of Lorem Ipsum: "Redacted" http://t.co/8A0LgrR1nS (23 Feb)
  • VisualizingOrg: Use #d3js and celebrate #opendataday by visualizing @worldbankdata in our Sprint: http://t.co/mTEHmV5v2P (23 Feb)
  • VeraSF: Mahout0.8-New and Improved with Super-fast Clustering(TM) http://t.co/DwazrkBVjl (23 Feb)
  • nicolastorzec: Classic intros to Unix power tools for text miners: Unix for Poets http://t.co/cvm7b1NpCB, Data-Intensive Linguistics http://t.co/hAaZebGzbs (23 Feb)
  • renelaennec: Apple launches dedicated ‘Apps for Healthcare Professionals’ collection http://t.co/6rVYKO9JN8 via @imedicalapps (23 Feb)
  • stefanjudis: Blog Engine in #nodejs... I'm looking for something like that very long. I'll give it a try tomorrow. #cms http://t.co/6olppqnC1c (23 Feb)
  • patrickDurusau: ...O’Reilly Book on NLP with Java? #topicmaps #nlp #java - http://t.co/HP3mQSbEdR (23 Feb)
  • renelaennec: Mining Electronic Records for Revealing Health Data http://t.co/9pPO07mCQB (23 Feb)
  • yokofakun: Bioinformatics Algorithms on coursera: https://t.co/Or1lb6YgDH (23 Feb)
  • revodavid: Intro to #DataScience eBook by @jfstn is great, free, and includes #rstats scripts to play with: http://t.co/mcEipMBhyH (22 Feb)
  • JeffClark: An excellent gallery of #d3js examples - http://t.co/hfPmXkm3lI by @d3visualization. (22 Feb)
  • JanWillemTulp: Good article RT @zachgemignani: Required reading for data analysts...What Data Can’t Do http://t.co/PBDvgHdlkK (22 Feb)
  • Bill_Gardner: The problems with clinical guidelines. http://t.co/f6lQp4zkzv (22 Feb)
  • cortesi: New post: Things I found on Github - pipe chains. http://t.co/5uz2klPxK9 (21 Feb)
  • zentree: The Magic Book Project: an open-source framework for the design and production of electronic and print books. https://t.co/reJeCi4Qu7 (21 Feb)
  • statsepi: Education in Epidemiology: "The Times They Are a-Changin'" : Epidemiology http://t.co/kOqZrqTb (20 Feb)
  • useR_2013: #rstats Tutorial at #useR2013: Predictive Modeling with R and the caret Package. http://t.co/00Ypq1Dp by Max Kuhn (19 Feb)
  • jonathanstray: Done! A complete course in computational journalism, from @jmschku. All lectures, readings, assignments online. http://t.co/NLRIOUpg (19 Feb)
  • jseabold: Trying out a new monospace font. (And some interesting factoids on the 'design' of OS X fonts - possibly outdated) http://t.co/BVa3l6q4 (19 Feb)
  • ProbFact: RT @stevenstrogatz #Cancer meets #math -> http://t.co/J6ia8GUc … Very readable survey; uses probability and branching processes (19 Feb)
  • BioMedCentral: RT @bmc_series: Prediction of a time-to-event trait using #genome wide #SNP data http://t.co/YpvbASL0 #genetics #bioinformatics (19 Feb)
  • XiXiDu: Free Book: Learning Statistics with R http://t.co/2ePiURqP (19 Feb)
  • DrDanielSwan: Paper: A powerful and flexible statistical framework for testing hypotheses of allele-specific gene expression from... http://t.co/rYadT52i (19 Feb)
  • bigmlcom: http://t.co/JeFtEpe0 Everything you wanted to know about #machinelearning but were too afraid to ask. Post on ml-fundamentals Part 1. (19 Feb)
  • neilfws: Always think calling one language from another is A Bad Idea. Then I find stuff like Rserve-Ruby-client and go "cool!" https://t.co/C4AzwZKx (19 Feb)
  • matic_meglic: Excellent article on #future #e-mentalhealth by Kathy. I'd just add #gamification @PaulLikeMe you still exist in 2030 http://t.co/1tVdjQtu (19 Feb)
  • neilfws: Bookmarked: Classification of Mislabelled Microarrays using Robust Sparse Logistic Regression http://t.co/i9Fs3MJq (19 Feb)
  • msgbi: http://t.co/1t54ilK7 (Interactive Vim tutorial) (19 Feb)
  • fperez_org: @hadleywickham ipython site updated to better convey project scope, added separate notebook page. thx for the prod! http://t.co/gUf79hwr (19 Feb)
  • cortesi: New post: Things I found on GitHub - shell history. http://t.co/bFJKueKH (19 Feb)
  • EpiExperts: Environmental #Epigenetics and Its Implications for Disease Risk and Health Outcomes (FIFY) http://t.co/yWrchEVq -CW (19 Feb)
  • Atabey_Kaygun: Git for Scientists: A Tutorial http://t.co/XFfnRaKc (19 Feb)
  • paulblaser: 10 R packages every data scientist should know about - http://t.co/OKmo56yQ (19 Feb)
  • albertocairo: 'Seven dirty secrets of data visualization' by @chartio & @ClearStoryData: http://t.co/VvHObGdg via @DesireeMPerry #dataviz #infographics (18 Feb)
  • arnicas: Kind of impressed by @jakevdp animation of lorenz attractors in 3d in matplotlib of all things http://t.co/mv5coOS1 (18 Feb)
  • jebyrnes: R. A. Fisher - the ultimate outsider, and revolutionary who built much of modern statistics http://t.co/HJccs5hF Man, what drama! (18 Feb)
  • moorejh: #bigdata #infovis #dataviz #bioinformatics RT @SocialBizIntel: The Beauty Of Data #Visualization http://t.co/v1NC9OeC (18 Feb)
  • SeanTAllen: "Drastically Improve Your #Python: Understanding Python's Execution Model" => http://t.co/lRGY2TRD (18 Feb)
  • JustGlowing: Visualizing the tangent with #python http://t.co/JkEgV6hj (18 Feb)
  • mdallastella: "Write Yourself a Haskell... in Lisp (17 February 2013)" http://t.co/qshoUUEP - recommended via @Prismatic (18 Feb)
  • klmr: My surprisingly popular “Don’t use f*cking pointers” presentation now available as HTML: http://t.co/plS6mxdP and PDF (just append “.pdf”) (18 Feb)
  • mja: What should we expect as sample sizes for cognitive ability GWAS get bigger? http://t.co/H3pxEIVM /by @timothycbates (18 Feb)
  • kaythaney: Great list of online tools for researchers from an MIT postdoc, working to increase awareness in his own lab: http://t.co/OBaB2CZ3 (18 Feb)
  • fperez_org: A collection of Notebooks for using IPython effectively: https://t.co/zwcElU6o (18 Feb)
  • newsycombinator: Slate: a Mac OS X window manager for power users http://t.co/NBHsuLci (18 Feb)
  • DrBunsen: Great ideas on generating reproducible data analysis pipelines with functional programming, makefiles, and /cache: http://t.co/gB2jhk7i (17 Feb)
  • transarchitect: If motivated you will do it now, if inspired you will do it forever. (17 Feb)
  • dailyjs: If you're interested in buying Alex's book (Node.js in Practice), here's a 50% off code: nodejspco http://t.co/dtJnSevb (17 Feb)
  • gawbul: Awesome :-) @trvrb: GitHub's #boxen (http://t.co/JhCsv2NX) looks like it could be pretty great for managing bioinformatics boxes. (17 Feb)
  • abmathewks: ExploringDataBlog: Finding outliers in numerical data http://t.co/ZWFwU696 #ExcellentPost (16 Feb)
  • mbostock: Added census tracts, block groups and blocks to the us-atlas project. A crop of New Jersey: http://t.co/SMZmebeJ (16 Feb)
  • hmason: great idea -- have your students replicate the statistical work in published papers http://t.co/PQlCADWr (16 Feb)
  • newsycombinator: Aggregating statistics in Clojure http://t.co/mdQkOc4O (16 Feb)
  • Atabey_Kaygun: Using LibSVM with python: http://t.co/fBl42szO (15 Feb)
  • zentree: The Why Axis. #visualization http://t.co/n7Tr5v4i (15 Feb)
  • revodavid: Replay of @revojoe's Intro to #rstats for #DataMining webinar, plus links to R scripts and data used in the demo: http://t.co/7y2D15df (15 Feb)
  • vsbuffalo: Huh, Wikipedia has a "Common misunderstandings of genetics" page. http://t.co/tH5o027S Still not as good as: http://t.co/rOoR43St (13 Feb)
  • neilfws: Bookmarked: Crackpot index http://t.co/N5ixcvoD (13 Feb)
  • HarlanH: Speak, Memory - great personal essay by Oliver Sacks about the fallibility of memory http://t.co/RQKioXEO (13 Feb)
  • yaaang: Some nice Postgresql tips from Instagram http://t.co/wHiHwB6J (13 Feb)
  • drewconway: Language Use on GitHub http://t.co/1FuP9DXB (13 Feb)
  • dontYetKnow: Just learnt about Carton (https://t.co/TTNKsVLr), the Elisp answer to Bundler. Explicit dependencies for your packages! #emacs (12 Feb)
  • zoltanvarju: Whirlwind tour of pandas in 10 minutes | Quant Pythonista http://t.co/InOADtoI (11 Feb)
  • bioontology: CollabRx Releases Semantic Clinical Support Tool for Oncologists http://t.co/GgqcKvjT (10 Feb)
  • fonnesbeck: Open-access publishing with F1000Research. http://t.co/0d8tyXXk (10 Feb)
  • emacs_knight: If you're a #git user you might find emacs-git-gutter useful https://t.co/liWvXDWz (10 Feb)
  • erlichya: @dgmacarthur Not so easy Daniel. MZ twin exhibit blood chimerism in 70% of cases. http://t.co/xqZc7DgL This would mask most of differences (10 Feb)
  • ForbesLindesay: A permalink to a diagram of a regular expression http://t.co/xNgiWUIU (Rendered entirely in your browser) (9 Feb)
  • druvus: displayHTS: a #R package for displaying data and results from high-throughput screening experiments http://t.co/jSuDNyZg (9 Feb)
  • isomorphisms: Free, unlimited (open soure) dropbox: http://t.co/K297UZB7 (9 Feb)
  • mathematicsprof: Common Mistakes in Discrete Math and Logic -> http://t.co/gbDysG5U #logic, #math, #mathed (9 Feb)
  • fjossinet: "Exploring web standards for high data density visualizations" http://t.co/BJSBFGP3 (8 Feb)
  • blattnerma: Sparse group lasso and high dimensional multinomial classification #machinelearning #lasso #classification http://t.co/f4g2ft2l (8 Feb)
  • AlecGaffney: The most powerful case for the biopharmaceutical industry you'll ever see, in one graphic: http://t.co/jV1AfSNR (8 Feb)
  • kdnuggets: Can Kaggle data mining competition winner be automated? Here is a proposal (if it works, general AI is not far behind) http://t.co/fGQBYYzF (8 Feb)
  • michaelaye: Beautifully laid out lecture on matplotlib by using downloadable and usable ipython notebook. http://t.co/fPUpvGXw (5 Feb)
  • johnmyleswhite: Two of my great loves combined by @Atabey_Kaygun: histograms and the Collatz conjecture. http://t.co/m3Gd1IXr (4 Feb)
  • SeanTAllen: "Simulant is a library and schema for developing simulation-based tests." => http://t.co/HNLFYcXy <= using #datomic and #clojure (4 Feb)
  • timelyportfolio: Great Visual Notes from Datavis Panel http://t.co/WXBiw62V (4 Feb)
  • arnaudsj: Redis and Lua: a NoSQL power-horse - http://t.co/IQJO3zKD (4 Feb)
  • romunov: Tukey, as the story goes, suggested the name “the shotgun” because you can blow the head off any statistical problem." http://t.co/OjVFAhL8 (4 Feb)
  • planet_lisp: Zach Beane: The Rob Warnock Lisp Usenet Archive http://t.co/aQ1oClwz (4 Feb)
  • planetclojure: Purely functional data structures in Clojure: Leftist Heaps http://t.co/FAJ1XgWF (4 Feb)
  • lucaborger: Ingenious visualization of Fourier series using wheels on wheels: http://t.co/Yz3WnunV MT @stevenstrogatz HT @kwinkunks #teaching (4 Feb)
  • victoriastodden: sorry for tweeting so late, but this is awesome: Winter School on "Reproducible Science and Modern Scientific Software" http://t.co/tHd6ZBEI (4 Feb) siah: All the videos from the past PyData conference are available online for free. http://t.co/dLbIlZCf #python #bigdata #smalldata (4 Feb)
  • erwtokritos: Stanford Personalized PageRank Project http://t.co/vfEZyJ5o #datamining (4 Feb)
  • Atabey_Kaygun: Natural Language Meta Processing with #lisp http://t.co/xzhHAqmO (4 Feb)
  • BillBarnhill: Useful emacs tips beyond the standard cheat sheets: http://t.co/E8bp4OP7 (3 Feb)
  • fonnesbeck: @mikedewar @arnicas You might take a look at conda: http://t.co/ghtQUbuZ (2 Feb)
  • Altons: A quick GNU R tutorial to basic operations, functions and data structures http://t.co/FXfNnRNd via #rstats (2 Feb)
  • triadsou: [Mixture models] / “The gradient function as an exploratory goodness-of-fit assessment of the random-effects distri…” http://t.co/i7jS38kv (2 Feb)
  • racketlang: Racket v5.3.2 is out! Ships with a new math library, bit vectors, a new (beta) package system, and more: http://t.co/srvDEJoZ (2 Feb)
  • ogrisel: Predicting Good Probabilities with Supervised Learning: <http://t.co/i2UdEuUK via the comments in this post http://t.co/JTW3dqlF by @sanity (2 Feb)
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