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

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

• smdiehl: Early draft of the OReilly’s “Parallel and Concurrent Programming in Haskell” http://t.co/xDmNxPVxwZ #haskell (29 Mar)
• hadleywickham: updated preprints: “graphical crit: some historical notes” http://t.co/Ny6DkVHEKP + review of stat graphics http://t.co/fy7JPCPGzv (29 Mar)
• hmCuesta: Increase Your Kaggle Score With a Random Forest: http://t.co/9mHRPzfx9a via @DataScience201 (29 Mar)
• genetics_blog: A practical data processing workflow for multi-OMICS projects http://t.co/gLlXqUGQdU #bioinformatics (29 Mar)
• siah: Python for Bash scripters: A well-kept secret http://t.co/XIegfvLzf2 (29 Mar)
• abmathewks: Anything but R-bitrary: Build a search engine in 20 minutes or less http://t.co/FaHr6dfzXe #rstats (29 Mar)
• zoltanvarju: Intoductory Machine Learning Textbook http://t.co/O8EkHvsWg3 (29 Mar)
• mdreid: New (non-ML) blog post: Switching from Jekyll to Hakyll. http://t.co/ORGQbA62au (28 Mar)
• freakonometrics: “Making friends with your data: Improving how statistics are conducted and reported” http://t.co/ZlEMtjTVD1 (28 Mar)
• ctitusbrown: Extremely Large Databases (XLDB) 2012 - Workshop report http://t.co/KqyYrKQXAv Lots of good stuff about biology in there. (28 Mar)
• mheadd: Scraping for Journalism: A Guide for Collecting Data. http://t.co/EbX2bc83L4 (26 Mar)
• tu_bd_libre: Tutorial de #PostgreSQL 8.4 http://t.co/noDxr7tw8b (26 Mar)
• dberkholz: New post | Programming languages ranked by expressiveness: http://t.co/EJuS5Mw4K1 (25 Mar)
• hmCuesta: MongoDB & Machine Learning http://t.co/chn7uNAWHs (25 Mar)
• revodavid: @Altons There’s a Data Step for #rstats in @RevolutionR called rxDataStep. Info in this white paper (direct link) http://t.co/FsAvZzY4it (25 Mar)
• siah: Python data tools just keep getting better http://t.co/DTjBatLeBl (24 Mar)
• SciPyTip: IPython creator @fperez_org wins 2013 Free Software Foundation award http://t.co/fmwHQo1Tnp (23 Mar)
• moorejh: #programming RT @hnycombinator: Practical algorithms & code optimization: maze generation http://t.co/Zloh9eVLwB (23 Mar)
• albertocairo: “It may be true that many arguments in visualization are petty. But in some cases, the stakes are high” http://t.co/E9ohxUYSBw @eagereyes (23 Mar)
• jjgibaja: Interested in #MachineLearning? Then you should consider taking this (excellent) course: http://t.co/jEf8lwZd6l #LearningFromData #Caltech (23 Mar)
• beaucronin: My (hopefully accessible) thoughts on Why probabilistic programming matters https://t.co/6jC3kwFPpn What think you all? (23 Mar)
• tdhopper: MapReduce Patterns, Algorithms, and Use Cases http://t.co/8NO9HgG06H (23 Mar)
• moorejh: The Joy of Stats (The Economist) http://t.co/jFzEx0Nsuo #datascience #economics (23 Mar)
• hmCuesta: Introduction to Parallel Programming GPU by Udacity https://t.co/OEBmzRW1ev (22 Mar)
• golifescience: SciPy Scientific tools for Python #computing http://t.co/RoURGDVBxZ (22 Mar)
• johnmyleswhite: Elementary data analysis from an advanced viewpoint: modes, medians and means done right. http://t.co/cY2baSOy31 (22 Mar)
• josh_wills: Some command line tools I wrote with Crunch that make Mahout easier to use for new data scientists: http://t.co/tayYRNIPRp (22 Mar)
• siah: Just Use Sublime Text Blog http://t.co/G2vxUc1CQB (22 Mar)
• cloudera: Cloudera ML: New Open Source Libraries and Tools for Data Scientists http://t.co/K0F1MG1znb (22 Mar)
• conjugateprior: The importance of making research accessible. HT @Stephen_Curry http://t.co/f1fdI5hBhM Don’t dumb down the research. Level up the audience. (21 Mar)
• kwbroman: Another #d3js #visualization example: a series of linked heatmaps. <http://t.co/UN6EAS9x3i http://t.co/GAsHqHoA1m (21 Mar)
• TWiecki: PyMC3 sneak-peek: http://t.co/Kcb8LvE592 http://t.co/pHksd3uJTp Uses Theano as a backend and implements Hamiltonian MC (like stan). (21 Mar)
• MongoDB: A Crash Course in MongoDB by @dirnonline from @PyCon http://t.co/YgpyjrBebl (21 Mar)
• moorejh: Great piece in @sciencemagazine by Horwitz et al. on (De)Personalized Medicine. http://t.co/Kcd3o7w796 #genomics #complexity #pm101 (21 Mar)
• ErgoEmacs: minor new look. 〈Xah Emacs Tutorial〉 http://t.co/R5knGSTerM (20 Mar)
• ialuronico: Some new features of feature importance ranking #R (party package) http://t.co/chhikBkxFX (20 Mar)
• neilfws: Bookmarked: biojs - A library of JavaScript components to represent biological data - Google Project Hosting http://t.co/wlz0LkbzHI (20 Mar)
• blattnerma: Distributed Learning of Gaussian Graphical Models via Marginal Likelihoods #machinelearning http://t.co/gcKAfzNTH9 (20 Mar)
• moorejh: RT @anirvan: Altman’s slides will be online tonight at http://t.co/fx7F5wLsb6 #TBICRI13 (20 Mar)
• DNADude: The human genome “connectome.” Very interesting paper http://t.co/hfYS4re3iQ (20 Mar)
• DataJunkie: An implementation of MARS for Python using pandas etc. https://t.co/nHn8AgnSck #PyData (20 Mar)
• seanjtaylor: “All the intuitions about how to assess a model are in this picture.” – @davidblei http://t.co/jcciPIiUk8 (20 Mar)
• recology_: “a package that lets you use #rstats objects as input for JavaScript visualizations” - #d3js http://t.co/3kcm1kvgcg (20 Mar)
• brinkar: Slides from my #pydata talk about @wiseio tech. Machine Learning from Fast to Easy https://t.co/u4CMgV1kAc (20 Mar)
• arnicas: “How to Scale a Code in the Human Dimension” by M Turk on open source communities of practice http://t.co/Fgp1iJhvLB via @fperez_org #pydata (20 Mar)
• arnicas: Super cool. RT @diegovalle: Here’s a quick way to create a 2d density map in #d3js http://t.co/sDeKlrni5Z (20 Mar)
• TrestleJeff: How to properly deprecate a function in an R package: http://t.co/S6QWFPdPXM #rstats (20 Mar)
• fhuszar: Attention Machine Learning and/or DataVis Geeks! Come participate in http://t.co/fgQkFwvuTw Two challenges with data provided by @PeerIndex (20 Mar)
• rkneufeld: If you’re attending my Emacs talk this morning visit http://t.co/RMsCUZhF28 if you want to be able to follow along. #ClojureWest (20 Mar)
• moorejh: #infovis #dataviz #bioinformatics #datascience MT @JamesLZ 20 Best Tools for Data #Visualization http://t.co/kO8p26AplF (20 Mar)
• dataJujitsu: 75 trials and 11 Systematic reviews are published EVERY DAY (circa 2010) http://t.co/d9F1kUFdwb Need for text-mining in medical research? (20 Mar)
• viatropos: Lots of nice color themes for sublime: https://t.co/stxZ1eFozX (20 Mar)
• SciPyTip: mpmath: pure Python library for multi-precision floating point arithmetic http://t.co/5gQHri15N3 (19 Mar)
• StatModeling: New post: Tibshirani announces new research result: A significance test for the lasso http://t.co/otOgX1oMe3 (18 Mar)
• FGRibreau: Great stuff // Debug #JavaScript right in #Sublime text editor http://t.co/X5mNldIEVa (18 Mar)
• gawbul: PLEAC - Programming Language Examples Alike Cookbook http://t.co/gwnlkI10ZW (18 Mar)
• rdpeng: Yihue Xie has some suggestions for statistical conferences, and they’re all good ones. http://t.co/GIAzLRtZtP (18 Mar)
• hgascon: The dilemma of being a scientist when everyone is asking for inventors… http://t.co/nXGmA5ldy6 (18 Mar)
• Wiley_Stats: The most comprehensive introductory-level presentation of modern geometry currently available: http://t.co/L61cqsd3hg (18 Mar)
• FGRibreau: Countable.js—live word-counting in JavaScript http://t.co/Rx2XCDrOGg (18 Mar)
• kdnuggets: OpenCPU - open source system for R web applications - Ajay Ohri interviews OpenCPU founder http://t.co/7vPo6IIdQU (18 Mar)
• siah: Probabilistic Data Structures for Web Analytics and Data Mining http://t.co/WAtqpniARG (17 Mar)
• TWiecki: Shogun #ML library 2.1.0 released: http://t.co/pCitkCaLtt (17 Mar)
• onethingwell: Type Zebra - Test your fonts in web browser. Preview locally installed fonts in the browser, with a handy… http://t.co/wpsn20JGUw (17 Mar)
• jiffyclub: Check out the redesigned Python home page: http://t.co/VrM9z57dZh #PyCon (17 Mar)
• traims: Bayesian Models for Complex Networks: slides (PDF): http://t.co/MAZeOpdMTk; exercises - http://t.co/2jQSQBpYnX (via http://t.co/8uYQrS81yv) (17 Mar)
• flash_us: #Closure tutorial http://t.co/pQkK5GcmJc (16 Mar)
• sclopit: Human Computation Must Be Reproducible http://t.co/9sIA4kcCSn (16 Mar)
• ivanov: awesome ipython notebook talk by @jiffyclub - here are his slides: http://t.co/MJNacv9Xfx (which is an ipython notebook!) #pycon (16 Mar)
• planetclojure: Angular Tutorial Rewritten to ClojureScript http://t.co/us4NZToq1Z (16 Mar)
• ctitusbrown: My #pycon 2013 talk: Awesome Big Data Algorithms http://t.co/gAqWxePHlO with slides, github repo, ipynb, and lots of ref links. (16 Mar)
• wesmckinn: Repo full of pandas tutorials for new users (as IPython notebooks): https://t.co/pEYsOdmHIX #pydata #pycon (16 Mar)
• awiltsch: Why are you using zsh or bash? Use fish. It’s pretty neat. https://t.co/yrNWdiVTvA (16 Mar)
• nhigham: Donald Knuth: “my education boiled down to 50% mathematics, 50% English” - http://t.co/JtvYUBxwfg Fascinating interview. (16 Mar)
• mja: A Beginner’s Guide to Scientific Misconduct by Montgomerie and Birkhead. Cf. the current ‘crises’ in psychology. http://t.co/FvcmiAWp1U (15 Mar)
• freakonometrics: “‘machines can grade writing exams about as well as humans” http://t.co/L8mzDjcWTr also http://t.co/cqkd74UT8H and http://t.co/fDV1anGSkV (15 Mar)
• ptaoussanis: #Carmine 1.7.0-beta2 is doing ~64,500 writes/sec on my 1.7Ghz MacBook Air (with pipelining) #Clojure #Redis (15 Mar)
• technomancy: Leiningen users: got time for another survey? https://t.co/C6k33eLSXg A few moments would be appreciated. (15 Mar)
• stevelosh: sure, try another mail client that’ll be acquired in 6 months. mutt doesn’t mind. mutt will always be there for you http://t.co/IYpUOzywJ2 (15 Mar)
• wuub: SublimeREPL coming to a Sublime Text 3 near you in not so distant future http://t.co/1UVcPMGgp1 (15 Mar)
• Viral_B_Shah: #julialang running in ipython notebook, with matplotlib plotting. Very cool. http://t.co/uhYcnqTiOe (15 Mar)
• walkingrandomly: Learn Python the hard way http://t.co/FxMXtbfMYv (15 Mar)
• genetics_blog: Improving the reuse of computational models through version control http://t.co/h86ibaFUUS (14 Mar)
• jandot: I see on +Eric Rochester’s github page that one of the data files for his new book on #clojure data analysis is… https://t.co/lZNopa3j45 (14 Mar)
• ethanwhite: Promising news for Python packaging? http://t.co/JydnPM8g6U (14 Mar)
• mikiobraun: Good post on a machine learning perspective on real-time predictive analytics http://t.co/YabmWCR6oZ (14 Mar)
• pgroth: Glue Viz - nice to see viz toolkits for python http://t.co/rpOpKkZ2Gi (13 Mar)
• technomancy: Finally ready to announce Syme, a side project of mine for collaborating on GitHub projects over SSH and tmux: https://t.co/98GH4gNHwM (13 Mar)
• genetics_blog: Patterns of population epigenomic diversity http://t.co/DthfmaBgmK (13 Mar)
• reid_jf: bbc doc A Decade of the Human Genome “Identifying genes is one thing … make a medicine that works is another” http://t.co/4efEbLfPvK (12 Mar)
• albertocairo: Yes: “Comparing pies and slope graphs as forms of data visualization” http://t.co/eCidWrxaaX by @VizWizBI #dataviz #infographics (12 Mar)
• PubMedHealth: We need to understand these basics about survival statistics http://t.co/MFSPi8PHSR Here’s why: http://t.co/UXc18hWdoA (11 Mar)
• Cmrn_DP: New post: How to sort “Top” comments like the Reddit and HackerNews pros: http://t.co/rN4JR3MBWq (11 Mar)
• siah: “Why it is important to publish source code and datasets for researchers?” http://t.co/ukJrjHmEKB (11 Mar)
• _quasi: refreshingly sweet! http://t.co/hV5NflGRpi .. #lisp (11 Mar)
• adolfoalvarez: online book “Using R for time series analysis” http://t.co/QqP87GkNRg (10 Mar)
• siah: PyMADlib: A Python wrapper for MADlib - an open source library for scalable in-database machine learning algorithms http://t.co/AJOrdYFxpV (10 Mar)
• mariofusco: Graph Databases http://t.co/tDmbncfGyA « free ebook (10 Mar)
• siah: Gaussian Process Tutorial http://t.co/5VG4hvGpx3 (10 Mar)
• HarlanH: http://t.co/JQITug4IOl > Storytelling with Data http://t.co/NGT5wMc4fm < Amazing presentation about NYTimes graphics. Wow. (6 Mar)
• modernscientist: R and pandas and what I’ve learned about each http://t.co/b9hNdQqBgL #rstats #pandas via @drewconway @fperez_org (6 Mar)
• cemerick: FYI, @ClojureBook is totally applicable to Clojure 1.5. Esp. if you’re coming from Java/Python/Ruby, now’s the time! http://t.co/KM3dJJ4HKg (6 Mar)
• drewconway: IPython notebook of @YhatHQ code comparing #rstats and #pandas via @fperez_org http://t.co/Fj4y9vWrdI (6 Mar)
• JanWillemTulp: “Selections in d3 – the long story” Great #d3js tutorial by @jcukier http://t.co/PKskiewOno (6 Mar)
• ConcejeroPedro: A course on Text Mining http://t.co/Or2G9rwfN2 (6 Mar)
• ConcejeroPedro: GReat! A coRRespondence analysis of your tweets using FactoMineR https://t.co/ZCsuZ5an5e (6 Mar)
• mja: The G-matrix is not enough: Indirect genetic effects from competition constrain life history evolution http://t.co/g53D36aAZb (6 Mar)
• ambrosebs: Hole-driven development http://t.co/7fje0ZVgGd Follow along with core.typed: https://t.co/YeqKGshNuB (6 Mar)
• geospacedman: @hadleywickham Maybe I’ll write geom_sp to use WKT in text in a data.frame column.. http://t.co/dcMRXimcUv (5 Mar)
• michaelaye: Filtergraph: A Web-based Data Visualization Application http://t.co/YpWGcOF6Wb (5 Mar)
• blattnerma: Sparse PCA through Low-rank Approximations #machinelearning PCA http://t.co/EuXkEJfe7r (5 Mar)
• planetclojure: Presentation: Clojure, Functional Programming and Data at http://t.co/01IN70wBZd http://t.co/4yqLi0mzM0 (5 Mar)
• vsbuffalo: Nice paper: “Population genetics of genomics-based crop improvement methods” http://t.co/jJUMM2cn8x (5 Mar)
• walkingrandomly: The latest mathematical software news. http://t.co/h53uDvwnVV with Python, R, NAG, Excel, LibreLogo and more (5 Mar)
• TrestleJeff: Publicly testing our Lung Cancer Explorer app. ‘Appreciate any feedback/bug-reports before we submit the manuscript! http://t.co/z5UWNQc6vK (5 Mar)
• albertocairo: Summary of @tapestryconf by @DataRemixed: Storytelling, data, visualization http://t.co/qjwSRJi937 #dataviz #infographics #iidviz (5 Mar)
• moorejh: STOP using just GO: a multi-ontology hypothesis generation tool http://t.co/eH2Y4BOqqc #bioinformatics #genomics (5 Mar)
• hadleywickham: functionals (aka for-loop replacements) in #rstats: https://t.co/BOa8PwsRpv. Learn about lapply, Map and friends. (5 Mar)
• mat_kelcey: “10-minute tour of pandas” by @wesmckinn http://t.co/YbH687Xqst (4 Mar)
• albertocairo: “A nice example where epidemiological/observational studies are later confirmed by a randomized trial” http://t.co/I3QCKxdE8m (4 Mar)
• arsduo: Amazed (but not surprised) that @mojombo’s 8-day-old toml project already has over 40 implementations. HT @parkr https://t.co/7hzSIzNVU1 (4 Mar)
• johnros2013: Dear Gmail… http://t.co/rZiDCXHKw3 (3 Mar)
• mspan: Wonderful essay about trade-off between bias and variance by Scott Fortmann Roe. #datascience #analytics http://t.co/kH3aduq8Ju (3 Mar)
• patrickm145: #d3js #dataviz folks should explore Kai Chang’s D3 blocks. Lots of amazing nuggets in there like this: http://t.co/CVAZmWm0pw (3 Mar)
• LaTeXTemplates: New #LaTeX template for a KOMA-Script Presentation. Check it out here: http://t.co/LjhSddfJJD Works great on @SpanDeX_io! (3 Mar)
• mhausenblas: http://t.co/WRajzXlNv8 Free Strata Reports #datascience #bigdata #strata (2 Mar)
• melpa_emacs: e2wm-R (20130302.2048) — some e2wm plugin and perspective for GNU R http://t.co/CzEI3wiM8b (2 Mar)
• moorejh: When Genetic Testing Can Be Dangerous to Your Health http://t.co/TSwoza6sXB #pm101 #genomics #genome #DNA (1 Mar)
• siah: MapReduce Patterns, Algorithms, and Use Cases http://t.co/jp2tvtVLKb (1 Mar)
• vijaykiran: Clojure and Clojurians at Factual http://t.co/YG6N2eCC3n (1 Mar)
• mbostock: Coordinated scatterplot and choropleth of population density & politics. Try brushing! http://t.co/aViDoaequP by @mtraven (1 Mar)
• SmartTypes: lessons from a recent kaggle challenge winner – @rouli using #pandas and #scikitlearn – http://t.co/SM29xfnxxT (1 Mar)
• revodavid: Resampling data from #Hadoop with #RHadoop - great guide from @laserson and video from @piccolbo http://t.co/OXBha6Uymd #rstats (1 Mar)