Here is the latest bag of tweets^*, which covers March 2015.

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

• DiegoKuonen: @janschulz @GregBufithis @chlalanne, + see >@robjhyndman’s #2 + #3: http://t.co/cRYM6XgvTO http://t.co/MyyxJVmkf4 http://t.co/nFbo6kc3xI (25 Mar)
• newsycombinator: The Racket Manifesto http://t.co/b2BNhjmuC4 (25 Mar)
• GregBufithis: For BEST explanation of how to distinguish data science from statistics see @DiegoKuonen: http://t.co/qr7ZD3pdmP http://t.co/Gw6NwwJbCp (25 Mar)
• modernscientist: TIL: IPython notebook now has multiple cursors. http://t.co/mh7JniIKIZ (25 Mar)
• JennyBryan: gspreadr: an #rstats pkg for Google Sheets Wld love feedback on functionality, usability. https://t.co/oB1W4Dybq4 http://t.co/JxCv4JltTd (25 Mar)
• noamross: Common errors in #rstats: an empirical investigation https://t.co/mi3pqA2NJh @swcarpentry @datacarpentry @drob (24 Mar)
• brentonk: The new lookfor R package by @thosjleeper looks great: https://t.co/6pF6SP2OFe. (23 Mar)
• tonyojeda3: Use Random Forest: Testing 179 Classifiers on 121 Datasets http://t.co/kEmSXZPpVt #DataScience #BigData (23 Mar)
• sarah_guido: This looks super cool: visualizing your music collection with Python. http://t.co/yxyS5oMeUb (22 Mar)
• nkeywal: I really like this schema in http://t.co/QxtFPDNIsf by @BaumerBen (via @bigdata). Nice separation of concerns. http://t.co/IhrkSrtmZL (21 Mar)
• SciPyTip: Epipy: Python tools for epidemiology <http://t.co/rNqWkbxgVH by @cmyeaton> (21 Mar)
• kwbroman: .@armish Unfortunately I’m more of a boutique professor. But see http://t.co/vjTnVqYSP8 (21 Mar)
• kwbroman: @stefanbache I live in 2001. Emacs was the thing. http://t.co/gXVsBamnVW (21 Mar)
• timelyportfolio: @hadleywickham also should point to work by @ireneros https://t.co/NzIZ4GfAnz (21 Mar)
• tdhopper: “Here’s a summary of the Python packaging landscape in September 2014” http://t.co/HKKaEzRMqz (21 Mar)
• larysar: Help needed (again): somebody to read my manuscript for English correction? https://t.co/NLbvduit4p (21 Mar)
• moorejh: #datascience RT @Rbloggers: broom: tidying statistical models into data frames http://t.co/J2Qvdq3LWF #rstats http://t.co/d7PMH0UVtn (21 Mar)
• hadleywickham: Someone should make a grid version of http://t.co/6XqE8kApMX #rstats (21 Mar)
• tableau: Good luck to @_deardata with their wonderful #dataviz project: http://t.co/z4pkveVomA (19 Mar)
• DiegoKuonen: Growing 1 tree > http://t.co/Z8HsQbI4lR … some trees > http://t.co/2EwBf0ChQE By @freakonometrics #RStats #rpart http://t.co/pDt9WLU0kf (19 Mar)
• treycausey: Deploy scikit-learn models and query them via a REST API. https://t.co/nL1LKEJhOp (19 Mar)
• statsforbios: GGally::ggpairs() looks pretty out there. http://t.co/16JELEyLvV #rstats http://t.co/73ZnvZnrSu (18 Mar)
• psych101: Part of the #psychology quotes collection: http://t.co/zYvERNB2D0 http://t.co/zkPZtjfB7Y (17 Mar)
• siah: I use sqlite for every small project and I recently found this lovely little tool for it -> “Browser for SQLite” http://t.co/jfebdd6Tb2 (16 Mar)
• stephensenn: @tslumley @chlalanne But sometimes the FDA takes decisive action in the journals http://t.co/3KWtc6JX3J (14 Mar)
• rasbt: Artificial Neurons and Single-Layer Neural Nets - How Machine Learning Algorithms Work Part 1 http://t.co/9NBW2R5tRr http://t.co/JtF4XKefWv (14 Mar)
• eddelbuettel: “Why drat?” Guest post by @shabbychef http://t.co/UQjykmFDif #rstats (13 Mar)
• genetics_blog: Anyone ever used any of the Caleydo tools? (Free, open-source) http://t.co/X97ayUQ6Ca (12 Mar)
• ds_ldn: Data Machina - a free weekly digest of data science curiosities and more… http://t.co/461QonymVi (12 Mar)
• abmathewks: Why haven’t robust (and resistant) statistics replaced classical techniques? http://t.co/wQi6ESXKMv (12 Mar)
• YhatHQ: R and pandas and what I’ve learned about each | #rstats #python | http://t.co/9cUdXZgEZl (12 Mar)
• hardsci: An open review of Many Labs 3: Much to Learn (new blog post) http://t.co/rswcj66TKG @BrianNosek @OSFramework (12 Mar)
• StatGarrett: I’ve made a new #rstats cheatsheet, Package Development with devtools. Get it here: http://t.co/zlVRHJgLfK http://t.co/TVIEX3DEkZ (12 Mar)
• mplappert: Surprises you find when reading through the SQLite code. Somebody must’ve received a lot of calls. http://t.co/1yTAvYLHMx (12 Mar)
• nicebread303: “A Compendium of Clean Graphs in R”: Guest blog post by @EJWagenmakers and Quentin Gronau: <http://t.co/e7wR2QAYjg http://t.co/QdkfzqEEwE (12 Mar)
• tslumley: “When the FDA finds significant [problems], those findings are seldom reflected in the peer-reviewed literature” http://t.co/tEOwQt4Gnd (12 Mar)
• robertstats: My slides for today’s talk at the UCL Farr Institute on turning #Stata #rstats into #d3js #dataviz http://t.co/qCcUusDuWZ (12 Mar)
• fjnogales: 5 data visualizations in 5 minutes: each in 5 lines or less of R http://t.co/vDhXCkfvpf #rstats http://t.co/8Jd0CPYq0r (10 Mar)
• BrianNosek: Many Labs 3 complete and under review! Manuscript, materials, and data available here: https://t.co/dFhHNjnRo4 http://t.co/KJg20yNkMR (10 Mar)
• HNTweets: Who Says C is Simple: http://t.co/rsJIjfkexK Comments: https://t.co/suMZAg7UbA (9 Mar)
• Soc_Net_Intel: RT @Stephane_Depres An overview of free software tools for data mining - https://t.co/uWTepfh8JV … #dataMining #Machinelearning #ML #bigdata (9 Mar)
• BartekDobija: http://t.co/N0cImikN7N - An open-source machine learning server for developers and data scientists #Spark, #HBase #Hadoop (9 Mar)
• DataTau: PyStruct - Structured Learning in Python: http://t.co/p9uuk1S0PD (8 Mar)
• data_wizard: #import.io | turns any website into a structured API without writing any code https://t.co/8P5DlPVfku #crawlers #extractors #connectors (8 Mar)
• KirkDBorne: Thousands of datasets for #DataScientists to explore: http://t.co/0okIB0jnfM #BigData #OpenData #Analytics via @bigmlcom (8 Mar)
• BigDataGal: #rstats #datascience Getting Data From An Online Source - (This article was first published on bRogramming, and… http://t.co/Zfks67yGPP (8 Mar)
• riannone: DiagrammeR v0.5 now available on GitHub. Make Gantt charts. Functions to help make graphs: https://t.co/7dEQX5XCRr http://t.co/obKAptCPIT (7 Mar)
• gappy3000: “A Survey of Statistical Methods and Computing for Big Data” #rstats http://t.co/ciUNHyMaly (7 Mar)
• ThomasSpeidel: @felixsalmon @tslumley this reminds me of percent change… Logs can help sometimes http://t.co/VhDYswYyzW (7 Mar)
• MathUpdate: My professor uploads his Set Theory (as well as his Combinatorics, Number Theory, and other courses) video lectu… http://t.co/zKuNDC93Kg (4 Mar)
• syhw: Another interactive gem by @karpathy : linear classification loss visualization http://t.co/NvHZydblk7 (4 Mar)
• MAG_Rx: Great documentary on #Tamiflu and the need to make all clinical data public, featuring BMJ’s @fgodlee #AllTrials http://t.co/gYkxn281KD (4 Mar)
• AriCitak: Migrating from SQL to MapReduce with MongoDB. #mongodb #MapReduce #sql #NoSQL #RDBMS #relational #databases http://t.co/b2rDqC0Aob (3 Mar)
• isomorphisms: Venerating Knuth = a status signal. Don’t confuse yourself and actually read TAOCP. http://t.co/WYySUZt6lu (2 Mar)
• aloraine205: Visualizing the genome: techniques for presenting human genome data and annotations http://t.co/dnJrcdngks #bmcbioinformatics (1 Mar)
• conjugateprior: Awk spanks Hadoop: http://t.co/HbKxHg64Bj HT @thegrugq (1 Mar)
• wj: #MapReduce for C: Run Native Code in #Hadoop http://t.co/EfbVQ0vtNL https://t.co/oGeIbm6BZJ (1 Mar)
• JustGlowing: 7 common mistakes when doing ML in practice http://t.co/NanzR8HJyL (1 Mar)
• bbatsov: People looking for a #Clojure web framework might have a look at the freshly minted Luminous 2.0 http://t.co/uysO3hPGpP (1 Mar)
• AriBFriedman: My most impt contribution to #reproducible rsrch: http://t.co/bV2U7N083T https://t.co/9nmSqugRn6 #rstats H/T @afrakt http://t.co/OVR3BwQpye (1 Mar)