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

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

• denislab: Convert org-mode to markdown with #emacs : M-x org-md-convert-region-to-md (26 Sep)
• cygri: I made a cheat sheet for doing SPARQL on the command line with Apache Jena: http://t.co/kAvS7aBdLb (26 Sep)
• ttscoff: And we’re off: Marked 2 is live. http://t.co/xgrF3Z3W5B (26 Sep)
• revodavid: R 3.0.2 released, improves documentation for both R and packages submitted to CRAN: http://t.co/4pfkJGOkG1 #rstats (25 Sep)
• robjhyndman: Forecasting with R http://t.co/1tnQvqJZUb (25 Sep)
• jhibbets: It’s not a MOOC, it’s not Moodle, and it’s not edX. It’s a GitHub for course creation: @coursefork | http://t.co/vXT2mlWg1h (25 Sep)
• rmcgibbo: @fonnesbeck if you’re looking for a change, check out https://t.co/cdfLk3kTVK HTML5 slides in markdown. (25 Sep)
• bzg2: Blogging from GNU #Emacs with #orgmode http://t.co/XL8UDqn63E (yes you can.) (25 Sep)
• kwbroman: Blog: Code review (a few more thoughts but still not very cleanly conveyed) http://t.co/zCXrd8qw2G (25 Sep)
• walkingrandomly: Lamenting the lack of multiple assignment in MATLAB http://t.co/IT2oLMnhCR (25 Sep)
• HNTweets: Vim’s full help in PDF form: http://t.co/HmmMW3kl8n Comments: https://t.co/iiwP0X4RU1 (25 Sep)
• kwbroman: “We need to get more code out there, not improve how it looks.” — @rdpeng http://t.co/qjschPLbFB (I was thinking the same thing.) (25 Sep)
• irr: Articulate Lisp - Common Lisp in 2013 http://t.co/LHVBBgv7Lg (25 Sep)
• moorejh: Parallel random forests http://t.co/QoVzU2lMWL #datamining #machinelearning #bioinformatics HT @webbedfeet (23 Sep)
• GENES_PK: Our paper on using PCA to test whether a variant is associated with one or more of many correlated traits is on ArXiv http://t.co/4onG6etgQC (23 Sep)
• StefanKarpinski: #IJulia notebook for the talk I gave at #StrangeLoop about multiple dispatch in #JuliaLang: http://t.co/ZU6oompaHe. (22 Sep)
• ErgoEmacs: Emacs: magit-mode Tutorial. beginner friendly http://t.co/EDIOMTYQ9G #git (22 Sep)
• zentree: ‘The cult of Bayes’ theorem’ http://t.co/6I2NMlBUot via @adzebill & @saniac (kind of). (21 Sep)
• sclopit: free lectures on quantitative economic modeling, programmed in Python http://t.co/MP5kjkhmlC (21 Sep)
• berndweiss: Applied Meta-Analysis with R (~ £58) http://t.co/IAe2SowanD #rstats #metaanalysis (21 Sep)
• berndweiss: (free) Tutorial On Meta-Analysis in R (UseR 2013) http://t.co/QMcK9QsK6e +rstats #metaanalysis (21 Sep)
• drago_carlo: Book by Dorian Pyle: Data Preparation for Data Mining http://t.co/BQQS8df6vD … via @jmgomez @kdnuggets @alexlang11 #DataMining #Book (21 Sep)
• ThembeK: Cheat Sheet: How To Work with Hive Functions in Hadoop http://t.co/dQuWVrU0s8 (21 Sep)
• ericnormand: Clojure videos? Yes, please! http://t.co/AqZndLnVw0 (21 Sep)
• hmCuesta: Data Analysis: Just one component of the Data Science workflow http://t.co/PBdnc8yF4M (21 Sep)
• gappy3000: Modeling data with functional programming in #rstats.Interesting throughout.Brian gets FP 4 data analysis. http://t.co/YIS45qafXy (21 Sep)
• SublimePackages: IPython Notebook: IPython Notebook plugin for Sublime Text 2 http://t.co/B1oe3SFXla (21 Sep)
• albertocairo: Nice visualization/analysis post by @driven_by_data “Analyzing bias in election polls with R” http://t.co/zL6I5gNgl4 #dataviz #infographics (20 Sep)
• zentree: ‘#Rstats, GeoJSON and GitHub’ http://t.co/L9H9SLGqPg (20 Sep)
• geospacedman: Dear #rstats users, take a look at the http://t.co/qMMkMtGoIV website, compare with http://t.co/taxHiGSHPc (20 Sep)
• genetics_blog: Gene set analysis integrating multilevel omics data http://t.co/UNDxrmKhkh #bioinformatics (20 Sep)
• cboettig: mine here: http://t.co/ZnXpnp0m2E RT @figshare: “Why don’t we make #data #sharing plans public to make sure researchers adhere?” #datacite (20 Sep)
• mbostock: So, like, what’s the difference between quantization and simplification in TopoJSON? http://t.co/9qgBefljZp (20 Sep)
• JustGlowing: Why are there so many Python implementations? http://t.co/QaUtLpwxZ9 (20 Sep)
• robanhk: This is a beautiful illustration of a kind of selection bias: Simpson’s Paradox http://t.co/C7oxrnOb2o via @vicapow (20 Sep)
• squartadoc: How to read a scientific paper…. brilliant http://t.co/W9LciQXads (19 Sep)
• jakevdp: Just finished the notebook for my “Efficient Computing with Numpy” lecture. All my knowledge distilled into one page: http://t.co/JNLyHoxNCW (17 Sep)
• gvwilson: Very useful: please may we have for Python and R source code? “@hmason: whoa, http://t.co/NIOfFIstB1 is very useful” (17 Sep)
• paulblaser: Big Data – When the ruckus is over, turn on the lights! http://t.co/rtqtnkZBtE (13 Sep)
• louisdorard: Nouveau livre sur le #MachineLearning et les #Prediction #API annoncé : http://t.co/Gy532l548o cc @ST4Good @TheDamfr @ogrisel @mathemagie (13 Sep)
• TWiecki: This is impressive: Free hosted IPython NB with real-time sync between browsers http://t.co/w2Ij93Eh8t Sign up: https://t.co/zKhe3pR9rQ (13 Sep)
• SublimeTxtTips: For a few days only: Download the current version of my #sublimetext ebook for free: http://t.co/meQSEY2Ydz Please RT! (12 Sep)
• writelatex: PNAS Journal LaTeX Template: https://t.co/xUSa1lsP0E via http://t.co/tkGz2R3Uzi (12 Sep)
• PLOSMedicine: “Is DSM-5 an improvement…? Yes, but perhaps not what we wished for at this stage in our field” http://t.co/D42SUCuGR9 via @BioMedCentral (12 Sep)
• Postgresapp: Postgres 9.3 is out with lots of awesome features https://t.co/a2ikGEfw55 update your Postgres.app here today http://t.co/dvIJU52nIH (11 Sep)
• gagliol: #NIPS13 workshop: Large Scale Matrix Analysis and Inference http://t.co/apDzfdOAhL (10 Sep)
• fperez_org: A Gallery of Statistical Graphs in Matplotlib: nicer plots than the default MPL produces, with all code: http://t.co/iyUT4rM5BI (10 Sep)
• ramnath_vaidya: Nice application of Slidify “@znmeb: It took me a while to get a clean workflow but I’ve published a bunch on http://t.co/1HJ8aJm3ze” (10 Sep)
• alphenic: http://t.co/q8I8r9a2TP (9 Sep)
• johannux: Analyse, visualise and interrogate data with these free tools: http://t.co/jyzk2vtbpa (9 Sep)
• stanfordnlp: Sentiment analysis beyond lexicons and bags of words! Demo of compositional deep learning for understanding http://t.co/xQ5AdYLq9X #nlproc (6 Sep)
• ConcejeroPedro: R VocabulaRy you should at least be aware that they exist: http://t.co/FuZ1P8UPJL by @hadleywickham gReat! (6 Sep)
• timelyportfolio: #rCharts #dimplejs + #AngularJS Controls: http://t.co/QR2zHyMbEM #rstats #d3js copied @ramnath_vaidya code http://t.co/hJhJCvhQCX (6 Sep)
• RDataMining: Slides & examples on using Shiny to build interactive web applications in R. Slides <http://t.co/B60Vm7XB1P; examples https://t.co/JIZFFdoWub (5 Sep)
• RDataMining: Introduction to Data Mining with R – slides in PDF of a talk at University of Canberra on 6 Sept 2013 http://t.co/z8bzXWfSTK (5 Sep)
• treycausey: cheat: create and view interactive cheatsheets on the command-line http://t.co/zP85MA495u (4 Sep)
• d3visualization: Miniviz: from Graphviz to #d3js https://t.co/kHONs2yzkz by @benbjohnson (4 Sep)
• kdnuggets: OpenML lets you search 576K machine learning experiments on 130 datasets http://t.co/CeK1ih9kd5 (4 Sep)
• eagereyes: New on eagereyes RT @eagereyes_feed: Another Look at Many Eyes, 18 Months Later http://t.co/vM9ZILCHDY (4 Sep)
• FILWD: … and here his classic Perception in Visualization: http://t.co/fm14FwueVJ (4 Sep)
• quandl: Fun with just-in-time compiling: #Julia, #Python, #R & pqR by @randyzwitch http://t.co/gicdTaIeKP #DataScience #Rstats (4 Sep)
• johnros2013: Useful tutorial to building an #rstats #Hadoop System - http://t.co/Siskrk2kf8 (4 Sep)
• vandy_biostat: Start Using Emacs http://t.co/u4x0RiFJ3H (4 Sep)
• CRANberriesFeed: New CRAN package influence.SEM with initial version 1.0 http://t.co/0QdYpl5sce #rstats (4 Sep)
• RDataMining: Results of KDnuggets 2013 poll on top Languages for analytics, data mining, data science: R ranked #1 again http://t.co/WzCmWqmtHS (4 Sep)
• ogrisel: Harvard Data Science class http://t.co/JCctfvjAUa is using #python & scikit-learn. Homeworks are IPython notebooks: http://t.co/prtlvs5JWc (3 Sep)
• mbostock: How To Infer Topology: a visual explanation of how TopoJSON works. http://t.co/8IoiTCdgwL (3 Sep)
• fonnesbeck: Using Python in Stata http://t.co/EIFA36Mn5z (1 Sep)
• DataWL: Knitr/Markdown OpenCPU App: A new little OpenCPU app allows you to knit and markdown in the bro… http://t.co/A2ueMroHes #bigdata #data (1 Sep)