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

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

• kaz_yos: tentative #haskell config for #emacs 24.4 https://t.co/bsGKY7Knm6 (26 Oct)
• gd047: Visualizing (generalized) linear mixed effects models with ggplot #rstats #lme4 http://t.co/2dLv6099xB via @strengejacke (26 Oct)
• mjane_h: Text Visualization Browser http://t.co/wqZekum9Z5 via @arnicas (26 Oct)
• ErgoEmacs: #linux ImageMagick Command Line Tutorial http://t.co/nTl39qO40C (26 Oct)
• mat_kelcey: @arnicas did you see chris’ interactive t-sne post? fun stuff http://t.co/DsmizxgEHB (26 Oct)
• sbrabez: Web-based IPython notebook http://t.co/KMxxJfmWCc in the cloud Wakario.io https://t.co/RYJ4GAB4GW #pyconfr (26 Oct)
• aronro: Command line one-liners: http://t.co/EnB0ctDArh & https://t.co/q9DwU0zPcl HT @jeroenhjanssens @chlalanne #Unix #Linux #shell #bash #tips (25 Oct)
• channingwalton: How did I not know about @fromPeerToPeer http://t.co/S1hIhOov2C Watch people as they work on a set problem. Via @sanityinc (25 Oct)
• modernscientist: Shell script info in Yosemite Notification Center http://t.co/pmpwlM9X4T My CPU/memory setup https://t.co/sCjTdWlj52 http://t.co/Q6AHsB4wNI (25 Oct)
• chacon: Sort of soft-launched the second edition of Pro Git: http://t.co/iDnBpKE8Ax, including new PDF, ePub and Mobi builds. Nice to be up to date. (25 Oct)
• GaelVaroquaux: Thoughts on succeeding in academia despite doing good software. http://t.co/yWoZEWGIer The slides of my @scipyconar keynote (23 Oct)
• Viral_B_Shah: @kaythaney Would you be interested in trying out #julialang with http://t.co/7QreV08FKR? Quite powerful for what you guys are doing. (23 Oct)
• Rbloggers: Why is my OS X Yosemite install taking so long?: an analysis http://t.co/cn5CC35BYQ #rstats (23 Oct)
• statsforbios: Yup. Super. RT @joffley: Best homepage I’ve seen for a while… great, contextual #dataviz to boot: http://t.co/Q4JbKXoYHU (via @chelozzz) (23 Oct)
• moritz_stefaner: @janwillemtulp indeed — see also http://t.co/dMS8pRQf0I (23 Oct)
• Atabey_Kaygun: New post: Hashes and Entropy http://t.co/ErzP1n4kCM (23 Oct)
• daringfireball: Gmail Inbox: http://t.co/jGMsr6Kdhh (23 Oct)
• wesmckinn: The next release of Pythran, a very interesting Python->C++ compiler, is out: https://t.co/qIt40y2IhW #pydata (23 Oct)
• JennyBryan: @hadleywickham ooh! subscribed and will look forward to it; car::recode() also some has some good ideas/inspiration (22 Oct)
• osxpeppermint: Peppermint is out! The most versatile Code editor for OSX. By coders. For coders. http://t.co/uhhD3YP7tD #osx http://t.co/OJknPmVUYQ (22 Oct)
• ptgmonteiro: “A biologist’s guide to statistical thinking and analysis” http://t.co/7lPWyq5eDs nice introductory review! (21 Oct)
• eddelbuettel: ICYMI: New littler release 0.2.1 http://t.co/IKZZEcQqwa Also new examples http://t.co/k4YS2czMVC #rstats (21 Oct)
• lbenitesanchez: JuliaOpt http://t.co/I47Sfztnaz (21 Oct)
• zentree: .@chlalanne I think Rcmdr or INZight are much better for teaching stats to the unwashed masses. https://t.co/0ZPpw8ENof (20 Oct)
• HNTweets: Fix macosx: https://t.co/axnsMnW0bQ Comments: https://t.co/xo9xBUeeEp (20 Oct)
• newsycombinator: Data Visualization with JavaScript http://t.co/SBtTLSL0vA (20 Oct)
• JanWillemTulp: +1 MT @andinfinity_GER: @filwd http://t.co/h8g55nfrws Sections ‘system fonts’ and ‘websites’ might help you. Awesome resource in general (20 Oct)
• thomasfletcher: Launched my new app this week: http://t.co/YmvjuuoS8T : A tool for automating tedious data extraction. (20 Oct)
• redditprogrammn: Datumbox open sources their machine learning framework http://t.co/t1oCTQTnMC (19 Oct)
• StephenPiment: Newly released: #matplotlib 1.4.1 #python #datavis http://t.co/0KskSrebpZ (19 Oct)
• zentree: “Bayes Rule in an animated gif” http://t.co/u1CiAx9Ua2 (19 Oct)
• bolkerb: recommendations for a minimal/super-compact CSL style (only 1 author, journal abbrevs, skip page nums,etc.)? http://t.co/BJMgcNpfBi (18 Oct)
• paulblaser: Data Sources for Cool Data Science Projects: Part 1 | The Data Incubator - http://t.co/xwoLuwLpoX (18 Oct)
• YhatHQ: Building Interpretable Classifiers with Rules using Bayesian Analysis | http://t.co/jPMW8I4hJi (pdf) (17 Oct)
• cyrillerossant: The recent release of NumPy 1.9 broke my Python software http://t.co/Xw3UxfaNSU cc @khinsen (17 Oct)
• JavaScriptDaily: An Introduction to D3.js: http://t.co/Ez23MWGMrt (this is good stuff) http://t.co/qbY8OxEePM (17 Oct)
• RegexTip: Lots of regular expression resources http://t.co/jnHTuJV1S0 (16 Oct)
• ds_ldn: Using knitr & pandoc to create reproducible scientific reports in R #rstats http://t.co/aQxKdDFs00 (16 Oct)
• jakevdp: How Bad Is Your Colormap? My latest post on Python/matplotlib dataviz https://t.co/o4XpSGR56o http://t.co/67CMBQBvVr (16 Oct)
• justmarkham: @YhatHQ Thanks for the tweet! I enjoyed creating that post and reference it myself all the time! Original: http://t.co/Id0ea1UTV0 (16 Oct)
• databrary: @glyn_dk You can find our user guide here: http://t.co/zlY9rGSxpc. We’re also writing a new guide that will come out in the next 2 weeks! (16 Oct)
• yukihr: What’s New In Emacs 24.4 - Mastering Emacs http://t.co/DxS8v42Q0k (16 Oct)
• MacDiva: And thanks to background windows in @fperez_org’s talk, I discover Gitter (Chat for GitHub): https://t.co/5h39wZrNRB #HHNYC (16 Oct)
• bolkerb: troubleshooting_conv http://t.co/ELfrjPkTHi (16 Oct)
• jseabold: Statsmodels 0.6.0 release candidate is available. Give it a spin. https://t.co/vVgJ1Ig7TG (16 Oct)
• redditprogrammn: Introduction to Functional Programming FP101x (Haskell MOOC) starts Today! https://t.co/futjwB8JUr (16 Oct)
• fonnesbeck: Epipy: Python package for epidemiology http://t.co/K4ZJziMtoB (15 Oct)
• misprintedtype: Explain git with d3 http://t.co/zc8HuSMM8w (15 Oct)
• DiegoKuonen: My (Updated) View on #BigData & #DataScience (in #Pharma): http://t.co/Kry4SKFZfu & http://t.co/bgS6XjUAjO #DataMining #Statistics (14 Oct)
• yokofakun: @neilfws opps … sorry, I deleted your post by mistake. Copy+paste from my inbox: http://t.co/DoSHHdfJcI (14 Oct)
• mja: @zentree Something like http://t.co/2EXwIH39yu for statistical analysis. (14 Oct)
• cfusting: Very interesting perspective on Neural Networks: https://t.co/VNmhRgSec3 (14 Oct)
• abmathewks: Scrape the Gibson: Python skills for data scrapers http://t.co/LXPAYc8gQr via @brianabelson (13 Oct)
• ctitusbrown: People interested in Project Jupyter/IPython Notebook: check out @ethanwhite’s profile in “My Digital Toolbox” http://t.co/UC4fGVVasK (12 Oct)
• GaelVaroquaux: Improving your programming style in Python – tips and tricks and references http://t.co/6f7noUrsHv (12 Oct)
• dsquintana: A dplyr tutorial for faster data manipulation in #Rstats http://t.co/c3E3uZfzbT Great resource from @justmarkham http://t.co/QLXwnZCyss (12 Oct)
• stanfordnlp: Stanford is back! :) RT @SylvainDeaure Dans la foulée de word2vec Stanford remet le couvert avec les vecteurs de mots http://t.co/mSE7uq2uU8 (10 Oct)
• mortenshogh: Just discovered one of the best emacs blogs ever. Go and read a couple of posts at http://t.co/8l5TE3wfBK (10 Oct)
• mja: Turning the GREML power analysis into R code if you need to run on lots of inputs https://t.co/6mlk8TJcLR (10 Oct)
• yokofakun: #biostar : Answer: A: Drawing Chromosome Ideogams With Data: New to me: (2014-10-09) via: @infoecho <https:… http://t.co/78IfqUv3Cs (10 Oct)
• octonion: Python 3.4.2 released today; it includes (finally) a statistics module. (9 Oct)
• j_kalla: Wow. What can we believe? Average sample size in social-personality research is 104. Power is 50% http://t.co/JWgfGHrlo5 (9 Oct)
• planet_lisp: drmeister: Debugging with the Clasp debugger http://t.co/nHyGEceTZg (9 Oct)
• visnut: Zoe Cheng talks “Visualize areal data via cartograms” using R, today’s working group meeting, slides at http://t.co/FQskzMdGEj (9 Oct)
• wesmckinn: IPython notebooks with refreshed code examples for pandas 0.15.0 thanks to @cpcloudy and co: https://t.co/587qpvc8Tj #pydata #pandas (9 Oct)
• Rbloggers: Fitting Lasso with Julia http://t.co/j0eVEURr0g #rstats (8 Oct)
• hseas: New visualization software uncovers #cancer subtypes from a vast repository of biomedical data http://t.co/XzXbE4Adtm http://t.co/MqxZUKAZr8 (8 Oct)
• fonnesbeck: QGrid is an extension that allows an interactive JavaScript interface to Pandas DataFrames in IPython notebooks http://t.co/GeyUeHh0wb (8 Oct)
• GitHubEducation: The best developer tools, now free for students: https://t.co/WJptY2hSdW (8 Oct)
• greghendershott: .@cristalopes Doh I forgot the link: https://t.co/JL5krcfKOV (7 Oct)
• FastCoDesign: Interactive chart tracks the narrative structure of “The Hobbit.” <http://t.co/HpQc9jQ1LT http://t.co/uLksA4Xezh (6 Oct)
• jsonstat: JSON-stat Viewer styles slightly improved to clarify that categories are not clickable http://t.co/5XyzAHdjG1 #jjt #viewer #validator #json (6 Oct)
• gnuhealth: #GNUHealth 2.6.4 is out ! https://t.co/mkQiZl31h9 (4 Oct)
• MarkedApp: Marked 2.4.6 is out on the MAS and automatic updates! http://t.co/mhDL5gdFPX (4 Oct)
• moritz_stefaner: csvkit is looking superuseful https://t.co/KozWgT1RPH (4 Oct)
• NatRevNeurol: New online this week: DSM-5 approach to classifying neurocognitive disorders. http://t.co/Nx9mBK1KTs #newfromnrneurol http://t.co/OC6bIM535N (4 Oct)
• alandipert: isomorphic CLI, REPL tasks and docs coming in the nascent boot2 #clojure build tool https://t.co/QPOtfdWOnv http://t.co/kPP9EPr9J4 (3 Oct)
• planetclojure: Clojure and Emacs without Cider http://t.co/pCtzM3fCMT (3 Oct)
• ttscoff: Answered: save your StackExchange discoveries http://t.co/MOuxEEOlSL [post] (2 Oct)
• pgroth: Awesome @synerscope viz using data from @Open_PHACTS work in @COMMIT_nl #bfod http://t.co/RtEOoigqV5 (2 Oct)
• analyticbridge: 10 most popular #datascience presentations on Slideshare: http://t.co/aOkDQDeiaN (1 Oct)
• seandavis12: Peter Humberg thorough tutorial of “Using knitr and pandoc to create reproducible scientific reports” in #rstats: http://t.co/aURhqDFNp0 (1 Oct)
• IanMulvany: Postgres full-text search is Good Enough! http://t.co/rlAE7Li6BA via @Instapaper (1 Oct)