Here is the latest bag of tweets^*, which covers June 2014.

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

• HNTweets: The new bower.io: http://t.co/ICUYGJqO1P Comments: https://t.co/2lpKcX0bI2 (27 Jun)
• jdudley: New paper: “Overcoming obstacles to repurposing for neurodegenerative disease” http://t.co/t3DnebsVz8 (26 Jun)
• tonyfischetti: Really cool visualization of posterior during Bayesian updating: http://t.co/93S1SlJEqv (26 Jun)
• tomstafford: Temporal structure of motor variability is dynamically regulated and predicts motor learning ability http://t.co/EYvmulLf54 Wu et al, 2014 (26 Jun)
• revodavid: @randyzwitch Luke Tierney talked a bit about potential optimizations related to row.names here at DSC (26 Jun)
• lukasvlcek: Very nice: Google introduced REST API for Gmail https://t.co/SdkAHsChLG (26 Jun)
• sachsmc: “tufte-style” handouts in #rmarkdown with this package. Supports html and pdf output (via tufte-latex). http://t.co/oFJaNE68qs #rstats (26 Jun)
• MacDiva: Sweet! @hadleywickham put his newest dplyr tutorial online: http://t.co/d6NTTD2PAH #rstats (26 Jun)
• josephmisiti: SVD in Ruby: https://t.co/4fbqpz6KN7 (26 Jun)
• TeXtip: Tools for LaTeX tables http://t.co/YxWw7pTZkl by @robjhyndman // updated link (26 Jun)
• Hyperion_HQ: Thoroughly enjoying reading pre-release PDF of “High Performance Python” by @ianozsvald and @mynameisfiber http://t.co/QiQVcwSgiQ (26 Jun)
• danieljpeter: Early look @ Learning Spark http://t.co/xSR1TugNdV by @holdenkarau @andykonwinski @pwendell @matei_zaharia < F-A-S-T! http://t.co/QnO8cSPLzt (26 Jun)
• Cmrn_DP: New! Data Origami: Level up your data skills with data science screencasts https://t.co/bzEdo5Qbg4 (26 Jun)
• StephenPiment: Very useful summary in a notebook. @PythonWeekly Getting the Best Performance out of NumPy http://t.co/cZNewQuxW5 #NumPy #Python (26 Jun)
• moorejh: Clinical face phenotype space - eLife http://t.co/VX9CtaEYzq #genetics #genomics http://t.co/4la1n2qTK6 (26 Jun)
• trebor74hr: Fenix Web Server | Static Web Servers for the Desktop http://t.co/czoTn3dLs9 (25 Jun)
• RPsychologist: Great presentation that shows why #d3js is awsome http://t.co/MqD50srbVr (25 Jun)
• genetics_blog: Search documentation for all #Rstats pkgs on CRAN, Bioconductor, and GitHub http://t.co/8TmfhYJZir (25 Jun)
• fitelson: Wolfram Research is about to put Mathematica online (for free). in fact, in essence, they already have…. http://t.co/4VjiAZaiIp (25 Jun)
• treycausey: @fonnesbeck watching a webinar right now, but http://t.co/sDN2PunbGy. (25 Jun)
• dataiku: Easy text clustering http://t.co/luoBCQ1soc (25 Jun)
• polesasunder: Using #dplyr with lots of joins to solve a stranger’s problem on SO. Send help http://t.co/JXpSnzAGg9 #rstats (25 Jun)
• philogb: Love the design for the new OECD better life index app by @moritz_stefaner http://t.co/jWbhaGjwpL http://t.co/MhVFC3emUX (25 Jun)
• juliabloggers: Using Julia As A ‘Glue’ Language http://t.co/NfiJYLaQRn #julialang (25 Jun)
• planetpython: Martin Fitzpatrick: Pathomx meets IPython - Workflow construction with IPython notebooks (and vice versa) http://t.co/TGJG2NsgkW (25 Jun)
• jmsidhu: Finding correlations in complex datasets http://t.co/uMAxSMr207 (25 Jun)
• Rbloggers: New! Search GitHub and Bioconductor packages on Rdocumentation http://t.co/sQ7lAbsNmc #rstats (25 Jun)
• lpfeed: “Data Structures as Code: The Joys of Meta-Programming. http://t.co/UVcfbYdcHB" (23 Jun)
• xieyihui: @kwbroman @tslumley Don’t panic. LaTeX typically embeds fonts. R PDF graphics can be problematic, but I have https://t.co/FaIRlMewiq (23 Jun)
• ogrisel: Adadelta by @mattzeiler looks like a very simple & efficient way to get automatic per param learning rates promising http://t.co/OQ6GW61Kt4 (23 Jun)
• modernscientist: Beaker: Python, R, Groovy, Julia, and Node in a browser-based notebook: http://t.co/7vSxsc1wqY Anyone tried? Overlaps w/ IPython notebook? (23 Jun)
• modernscientist: @DrBunsen Re: Pandas and big data, there is also Blaze https://t.co/aEgYmTJ0Mm (23 Jun)
• duchessfr: Rencontre avec @ogrisel sur Predictive Analytics #USI2014 #bigdata #machinelearning #scikitlearn http://t.co/BGwhFreQHZ (23 Jun)
• dataiku: #MachineLearning real-life isn’t Kaggle competitions – http://t.co/U8tFWKVmHS – “cleaning up data can take 80% of your time” (23 Jun)
• CasalsTMarti: Biostatisticians: Do You Know What They Do? http://t.co/j2RODSACmk (23 Jun)
• newsyc20: Unusual applications of Bayesian reasoning [pdf] http://t.co/gIU9jm8kal (<http://t.co/UZHXfwRio6) (23 Jun)
• kejames: Wow. h/t @gwmck RT @golan: Just learned about Japanese visual multiplication (counting intersections); mind blown. http://t.co/DAyMqc4jVT (23 Jun)
• newsyc20: Wolfram Language Introduction for Programmers http://t.co/ZdO2BoxEjN (http://t.co/PhT5GHiTTT) via @ColinTheMathmo (23 Jun)
• jedisct1: On wildcard expansion, one thing I’ve been doing forever is touch -@ (in ~, / and other sensitive areas) to cause rm -fr * & co to fail. (22 Jun)
• HNTweets: Torch7 – Scientific computing for LuaJIT: http://t.co/KcFXne4Qs5 Comments: https://t.co/PxOt0Hs7Kr (22 Jun)
• golovashkin: @JohnDCook Folks often intermix R with C/C++ for performance http://t.co/07qBWtztBz I love conciseness of R progs + http://t.co/bPqEwvj0JY (21 Jun)
• ErgoEmacs: a comparison of Syntax Coloring in Editors: #emacs #vim gedit. show your screenshot http://t.co/6NQ0PpmtRq (21 Jun)
• EMR_research: Clinical documentation improvement for outpatients by implementing electronic medical records. http://t.co/xOxTa2waFi (21 Jun)
• Stata: Want to publish books about #Stata or #statistics? StataCorp has a FREE #Author Support Program that can help! http://t.co/yeDLJteh0M (20 Jun)
• ds_ldn: Repository for UC Berkeley’s “Introduction to #datascience " course Spring 2014 https://t.co/UREc1IkukI (20 Jun)
• ds_ldn: Parallel Computing for #datascience w/ Examples in R and Beyond http://t.co/BgpxdlkJ67 by @matloff at UCLA (20 Jun)
• PhilBirnbaum: New post yesterday: How the phrasing “not statistically significant” falsely implies the absence of an effect. http://t.co/nvko6qWy6V (20 Jun)
• YhatHQ: Nice! docopt for R!! edwindj/docopt.R | http://t.co/sWJfRo5qAG thx @edwindjonge (20 Jun)
• SciPyTip: Binstar http://t.co/HbcnCsUfNT (20 Jun)
• JanWillemTulp: Mac Lovers and Data Storytellers Take Note! Tableau 8.2 Available Now http://t.co/BUNbBXOOUd (20 Jun)
• writelatex: A quick introduction to LaTeX by @vermiculus - great for learning by example: https://t.co/dj221TdCJV (20 Jun)
• dataJujitsu: New @PLOSONE paper on my #clinicalcodes #opendata #EMR repo: http://t.co/NQlmRVCxqR - code on CRAN, drafts on @github, data on @figshare #OA (20 Jun)
• moorejh: Estimating the predictive ability of genetic risk models in simulated data http://t.co/V9rcdWwB0z #genomics #GWAS #bioinformatics (20 Jun)
• medcodes: #ClinicalCodes: An online repository to improve validity and reproducibility of EMR research. Published in @PLOSONE http://t.co/DYeienTk5p (20 Jun)
• moorejh: This is a very nice comprehensive review of using #GWAS results to predict disease http://t.co/4hWkyJ4VCb #health #healthcare #genetics (20 Jun)
• statisticsblog: Working on a system that can show multi-threaded conversations. Doing a trial with the #rstats #rhelp archives: http://t.co/Hfcaexogzd (19 Jun)
• golovashkin: Julia: High-performance computing programming with ease https://t.co/IZG9lTcXKO (19 Jun)
• JoergR: Really? There’s a Python profiler built into IPython with the %prun magic? How did I never find this before? (19 Jun)
• YvesMulkers: Book: Data Classification: Algorithms and Applications http://t.co/DoqSe7nF2C (19 Jun)
• mxlearn: Machine Learning for Clinical Data Analysis and Healthcare [NIPS 2013] http://t.co/4SPrPXGQkX (19 Jun)
• statsforbios: I storified my #glm explanation. http://t.co/8YQq3pwzCQ (19 Jun)
• moorejh: Machine learning-based prediction of drug–drug interactions - JAMIA http://t.co/U31w9lj32k #genomics #informatics #bioinformatics (19 Jun)
• aalmiray: heads up @PacktPub authors, there’s a new template in town: #asciidoc http://t.co/mtAyaImXjE (19 Jun)
• HNTweets: RawGit – serves raw files directly from GitHub with proper Content-Type header: https://t.co/0WVUuKEzdA Comments: https://t.co/8NLG8KH7fn (18 Jun)
• zoltanvarju: Finding structure in xkcd comics with Latent Dirichlet Allocation http://t.co/4buRgGaVqF (18 Jun)
• KirkDBorne: A Tutorial on Statistical-Learning for Scientific Data Processing: http://t.co/fdVuj4kxlx #BigData #DataScience #MachineLearning #Python (18 Jun)
• ucfagls: New on my blog: “Simultaneous confidence intervals for derivatives of splines in GAMs” using simulation #rstats http://t.co/3IrrpjTkDY (17 Jun)
• YhatHQ: Theming IPython | http://t.co/SpBfqAnhcc (17 Jun)
• DiffusePrioR: Every empiricist should read this paper: “A Practitioner’s Guide to Cluster-Robust Inference”, http://t.co/ipv9TrqHJy #economics (17 Jun)
• StackTeX: Great answer: What is the Necessity of $…$ Around Numbers? http://t.co/CV48dGgF4K #mathmode (17 Jun)
• tyldurd: how to automatically retrieve and track new remote branches with git? #git (17 Jun)
• aria42: Conceptually really like Mondrian Forests, but only really work in low-dimensional spaces, which rules out what I do http://t.co/mpTjvpaI3B (17 Jun)
• StrictlyStat: fslr: An R Package Interfacing with FSL for Neuroimaging Analysis http://t.co/9Er8rQHzv6 (17 Jun)
• treycausey: I wrote about how we use contextual bandits to optimize customer experience @zulily. http://t.co/hQxdlwaSIN (17 Jun)
• michaelwaskom: We’ve released PySurfer 0.5 with some nice enhancements and new docs! More here: http://t.co/mzmlv2EXif http://t.co/5CLbYspUYp (17 Jun)
• walkingrandomly: Reproducing MATLAB random numbers in Python http://t.co/7joVC3kdbi (17 Jun)
• Soc_Net_Intel: #rstats : a nice and interesting french website on R done by Aymeric Duclert here : http://t.co/PNIF5TUJOB (17 Jun)
• cboettig: .@arfon Enjoyed your piece about jsonld for code metadata http://t.co/F6AGthch9y but not clear where u want feedback.. opposed to disqus? (17 Jun)
• SunWC: Munsell Color Wheel. http://t.co/q7BXC7fpQb Munsell Renotation Data. http://t.co/acQ1XSUvmi Munsell spinning top. http://t.co/ApXB7hjXOe (17 Jun)
• lpfeed: How to Make a Cube Plot with Gnuplot: Another example that shows how you can make gnuplot do anything. http://t.co/eAB3fFugZn (17 Jun)
• UnixToolTip: An Awk Primer http://t.co/H8ZocGgeA9 (17 Jun)
• opensourceway: Collaborative science writing made easier with JotGit by John Lees-Miller | http://t.co/jddg13XGgy (16 Jun)
• trent_hauck: A Vagrant box for Python data work: https://t.co/ftDNZD02UC (16 Jun)
• zoltanvarju: Gibbs Sampling in Haskell http://t.co/zfLlzjQfGD (15 Jun)
• Aelkus: Learning discrete math through functional programming http://t.co/LTn52mTSkG @Brett_Fujioka @faineg @rejectionking (15 Jun)
• inesgn: Useful and clarifying series of reads on frequentism & Bayesianism, with application in python http://t.co/O9prMm1N0z vía @jakevdp (15 Jun)
• gappy3000: Building an automatic statistician http://t.co/2Hs9Eo1u2m http://t.co/fxY4du7FUV (15 Jun)
• JanWillemTulp: http://t.co/IA1VHsCjiW Mirador, provides an overview of large datasets, by visualizing dependency structures and explanatory variables (14 Jun)
• planetclojure: Tools for Learning Clojure, Part III: Nightcode http://t.co/foDZmpvn39 (14 Jun)
• hackernewsbot: Wilson’s Algorithm… http://t.co/fEarThIBSw (14 Jun)
• YhatHQ: 7 Python Libraries you should know about by @HackerSchool alum, Dominik Dabrowski | via doda.co | http://t.co/eSwVqlQF74 (14 Jun)
• tonyfujs: R you ready to ggplot2? Slides & Code from my #EERS14 workshop are now on-line #Rstats http://t.co/9dAvYLHALo (13 Jun)
• bzg2: I released #emacs #orgmode 8.2.7 – enjoy! http://t.co/zet5U53FCs (13 Jun)
• tableau: When was Twitter “happiest” during #BRAvsCRO in #Worldcup? http://t.co/r01de1aqcD http://t.co/uBLinBGqV1 (13 Jun)
• Peter_Tennant: ‘Minimum Clinically Important Differences using raw (VAS) data, or (VAS) change scores in general, are meaningless’ http://t.co/rOrT5v2TI5 (13 Jun)
• pavelfatin: Free programming books - simply awesome: https://t.co/CTP6yuumD1 (13 Jun)
• newsyc250: Cross-platform Rust Rewrite of the GNU Coreutils https://t.co/IB0ee4NIuH (http://t.co/clrsW9d9sm) (13 Jun)
• fMRI_today: Vince Calhoun and The Mind Research Network are putting on a Schizophrenia Classification Challenge. Any takers? https://t.co/KVTAS6CYDU (13 Jun)
• YhatHQ: Data Structures for Statistical Computing in Python | slides by Wes McKinney for SciPy 2010 | http://t.co/nGsXSBVPJt (13 Jun)
• moebio: @wattenberg just featured a words cloud built with http://t.co/BXKYT133pF confirmed: RAW is the new ManyEyes (12 Jun)
• jakevdp: My diatribe for the day: Confidence, Credibility, and Why Frequentism and Science Don’t Mix http://t.co/SNrgGEXiV0 #IPython #DataScience (12 Jun)
• ramnath_vaidya: Interactive Documents #slidify + #rCharts + @OpenCPU http://t.co/QjfyO1lkmo #rstats learn more at User2014 tutorial. http://t.co/YPWUiCzp8J (12 Jun)
• TwitterOSS: new book: “Programming MapReduce With @Scalding” #hadoop https://t.co/ORpj0urILn (12 Jun)
• geomblog: Good practices in “modern” LaTeX (via +John Regehr). An excellent set of tips, many of which I did… http://t.co/OQPDnpYEvN (12 Jun)
• statalgo: “The Latest and Greatest Pandas Features (since v 0.11)” http://t.co/cjfZnfHnpR #python (12 Jun)
• siah: A Unified Architecture for Natural Language Processing: Deep Neural Networks with Multitask Learning http://t.co/MXijJ2dYRW (12 Jun)
• YhatHQ: MPLD3: Bringing matplotlib to the browser. A Linked Brushing Example | http://t.co/BsqEop2sKq (12 Jun)
• balajis: An API to publish machine-readable papers: http://t.co/HIDjp0ngt6 Of interest: @dgmacarthur @ctitusbrown @markkaganovich @eperlste @erlichya (12 Jun)
• YhatHQ: 100+ Interesting Data Sets for Statistics | http://t.co/K7swbwuH6R @robbseaton (12 Jun)
• DataTau: Introduction to machine learning book: http://t.co/ubEfEste1F (12 Jun)
• zevross: Wow extremely useful: pre-extracted @openstreetmap data for major cities, http://t.co/m78C43VB2U. Thanks @michalmigurski (12 Jun)
• YhatHQ: Outlier Detection via Markov Chain Monte Carlo | Bugra Akyildiz | @bugraa http://t.co/sxwzr9o3V7 (12 Jun)
• rasbt: My matplotlib plots are in IPython notebooks now, maybe useful to one or the other!? :) <https://t.co/FjtEcsrAPy http://t.co/r91SrqxQR5 (12 Jun)
• TrestleJeff: If you missed it, the shinyapps.io Alpha is now open to the public. Go grab your account name. https://t.co/MLVScd46Us #rstats #rshiny (12 Jun)
• moorejh: #bigdata #machinelearning RT @mAlmenea: The #DataScience Clock | http://t.co/hzs8d7kmXK http://t.co/PEDWkelXjl (12 Jun)
• hadleywickham: shiny docs = rmarkdown + shiny + easy = dead simple interactive reports. http://t.co/8oAvL8ZW9G #rstats (12 Jun)
• SciPyTip: Scientific Python lecture notes http://t.co/rLeiKlo0fK (12 Jun)
• enthought: Great matrix cheat sheet for MATLAB, Python, R and Julia. http://t.co/Cyy5RF6la7 (12 Jun)
• YhatHQ: Greg Lamp - ggplot For Python - YouTube vid | @theglamp http://t.co/uGA8fXZanj (12 Jun)
• kdnuggets: Huge Big Data Poster and Reference http://t.co/vSQpvM5s0P (12 Jun)
• phylorich: This. Is. Amazing. https://t.co/goEuWBV5v6 (via @_inundata) http://t.co/3BvPYVxjLT (12 Jun)
• PLOSLabs: Want to turn your scientific research data into #opendata? Check out this free handbook from @OKFN: http://t.co/Qm4CUp1Fc3 (12 Jun)
• ErgoEmacs: #Emacs Searching for Text in Files (occur, grep, rgrep, lgrep, grep-find, find-dired) http://t.co/1o7F2TAtsX (12 Jun)
• GilbertLiou: IPython Slideshows will change the way you work | Hannes Bretschneider: http://t.co/nlcIATZiQ1 (11 Jun)
• jmgomez: A Tour of Machine Learning Algorithms http://t.co/NIB3T4vrV5 #datamining (11 Jun)
• sammthomson: looks interesting RT @StatsPapers: Mondrian Forests: Efficient Online Random Forests. http://t.co/gLK4IDoFy0 (11 Jun)
• joe_pickrell: Displays P-values, priors, and relevant functional annotations learned from fgwas (https://t.co/xFwOaIMdWf) for 10 traits w/ public GWAS (10 Jun)
• joe_pickrell: First project in the lab by @tomaz_berisa was to build a GWAS browser: http://t.co/9dluCARn73 (10 Jun)
• HarlanH: I hate polynomials http://t.co/kXkSybY8wa < #statistics Gelman on problems with polynomials in modeling (10 Jun)
• hadleywickham: tidyr: reshape2 rethought for easier data tidying and elegant combination with dplyr pipelines: https://t.co/hmRD4qfGhX #rstats (10 Jun)
• jeroenhjanssens: Of course you can do machine learning at the command line! http://t.co/04DtrgV0DL (10 Jun)
• leinreleases: Leiningen 2.4.0 is out, now with a release task. https://t.co/Jba3Wlum07 (10 Jun)
• mcxfrank: This is why I love #Rstats: SCheck (cheating detection algorithm) is implemented in the MiscPsycho pkg http://t.co/2tqlPX8X8P (10 Jun)
• sureshone: Data Science Studio: Yuzu version released - Dataiku - http://t.co/biO2fpeOXn (10 Jun)
• plotlygraphs: .@SahaSurya @scikit_learn Interactive classifiers comparison, made by @etpinard in #Plotly https://t.co/XZWxxphcDt http://t.co/GGz3Nk9Z2c (10 Jun)
• revodavid: Catch up on the R news from the Revolutions blog with the latest monthly roundup: http://t.co/lcfmzCYRI3 #rstats (10 Jun)
• Soc_Net_Intel: #rstats : Data Munging, Exploratory Data Analysis, and Feature Engineering http://t.co/huJ8gxS5EW -> @simplystats @rdpeng @jtleek @bcaffo (10 Jun)
• pathogenomenick: homebrew-science: very helpful! https://t.co/sx4cbta3Jc (10 Jun)
• jakeporway: Awesome! RT @jeroenhjanssens: Look at what @OReillyMedia got me for my birthday – the cover of my upcoming book! http://t.co/nTBSm19wVu (10 Jun)
• moorejh: An outstanding paper on the context-dependent effects of #GWAS hits - need more of this! http://t.co/vRTBtBXu8e #complexity (10 Jun)
• writelatex: Have you created a poster using LaTeX? RT via @NPHatton Produced using WriteLatex: https://t.co/rrUK1wk5fj … http://t.co/I0ozc32GUk (10 Jun)
• treycausey: Getting started in data science: my (longish) thoughts. http://t.co/uLW0JSxWJ3 (8 Jun)
• jakevdp: A followup to my Frequentism/Bayesianism post: when the approaches give different results http://t.co/ITjLt1IgUw (7 Jun)
• KirkDBorne: R Cheat Sheets (by @Mark_Graph) - beginning, intermediate, & advanced R programming tips: http://t.co/Mc4aThHF1v #DataScience #Rstats (6 Jun)
• walkingrandomly: The Ipython notebook is coming to iPad. http://t.co/220KryuaGc This could be awesome! (5 Jun)
• cboettig: Great post from @bolkerb on “Is statistical software harmful?” http://t.co/5W4LMW748O on the @DynamicEcology blog. http://t.co/1W9m9XuIWQ (5 Jun)
• YhatHQ: First Chapters: visually describing writing styles w/ word counts. The longer the sentences, the larger the drawing. http://t.co/JYncEjpA05 (5 Jun)
• HlthAnalysis: Health Intelligence resource: Data sources http://t.co/WWyIBfFN9g #healthdata #hdpalooza #opendata #publichealth (5 Jun)
• dartdog: This Python For Data Scientists IPython Notebook looks pretty awesome http://t.co/xusLP7gbxz (5 Jun)
• kdnuggets: Pentaho Data Science Pack operationalizes use of R and Weka #rstats http://t.co/rzFuRsqpFT (5 Jun)
• kara_woo: Awesome! RT @carlystrasser: Great resource - overview of #datamanagement best practices, edited by @john_kratz: https://t.co/EOjVUwbcRu (5 Jun)
• recology_: useful things: unicode lookup http://t.co/JVt4ZXKFzj (5 Jun)
• YhatHQ: A gallery of interesting IPython Notebooks | http://t.co/4kZfeRzy5I (5 Jun)
• MiquelNoguer: “@StatFact: Four views of statistics: Frequentist, Bayesian, Likelihood, Information-Theoretic http://t.co/jDRuQgj8Ko” RT (4 Jun)
• cpsievert: Visualizing #ggplot2 internals with #shiny & #d3js: Blog post — http://t.co/GHkhEP8VLo Link — http://t.co/K854OUlQ3l http://t.co/Gs9nSirJNW (3 Jun)