Friday, April 22, 2016

Weeky Review 22 April 2016

Some interesting links that I Tweeted about in the last week:

  1. Difficulties of frequent moves, a hazard for academics: https://www.insidehighered.com/advice/2016/04/15/difficulties-constantly-having-move-academic-essay  Part of why being a postdoc sucks http://computational-intelligence.blogspot.com/2012/09/on-being-post-doc.html
  2. Developers guide to Facebook's Messenger chatbot: http://siliconangle.com/blog/2016/04/13/developers-roll-your-own-facebook-messenger-bot-and-what-you-can-do/ 
  3. Why it's important for PhD students to blog: https://www.insidehighered.com/blogs/gradhacker/blogging-establish-your-digital-identity  Other ways to establish an online profile: http://computational-intelligence.blogspot.com/2012/04/building-online-presence-as-academic.html 
  4. My final paper for IJCNN 2016: "Sleep Learning and Max-Min Aggregation of Evolving Connectionist Systems" http://mike.watts.net.nz/SleepLearningMaxMinAggregationECoS.pdf 
  5. Machine learning detects 85% of network attacks: http://www.theregister.co.uk/2016/04/18/ai_bot_spots_hacking_attacks/
  6. Paper on the AI^2 machine-learning based network intrusion detection system: https://people.csail.mit.edu/kalyan/AI2_Paper.pdf 
  7. Using deep learning to detect cancer cells in blood samples: http://newsroom.ucla.edu/releases/microscope-uses-artificial-intelligence-to-find-cancer-cells-more-efficiently 
  8. Recognising hand-written Japanese text with deep learning: http://www.bloomberg.com/news/articles/2016-04-13/artificial-intelligence-s-next-phase-sooner-and-more-accessible-for-everyone 
  9. A list of deep learning tutorials and resources: http://www.datasciencecentral.com/profiles/blogs/11-deep-learning-articles-tutorials-and-resources 
  10. Introduction to deep learning for chatbots: http://www.kdnuggets.com/2016/04/deep-learning-chatbots-part-1.html
  11. Gender diversity in AI: http://motherboard.vice.com/en_au/read/can-ai-help-gender-diversity-help-ai
  12. List of 15 machine learning frameworks: http://www.kdnuggets.com/2016/04/top-15-frameworks-machine-learning-experts.html 
  13. Yet another article on the AI^2 system: http://techemergence.com/an-ai-cybersecurity-system-may-detect-attacks-with-85-percent-accuracy/ Machine learning in security isn't that new, it's been done for years.
  14. Adding on-board intelligence to thermal cameras: http://www.theverge.com/2016/4/19/11459182/flir-movidius-boson-thermal-camera-computer-vision
  15. An ontology of machine learning methods: http://www.datasciencecentral.com/profiles/blogs/machine-learning-ontology 
  16. Guide to data analysis in Python: http://www.kdnuggets.com/2016/04/datacamp-learning-python-data-analysis-data-science.html 
  17. Randomized Forest ensemble method: http://www.datasciencecentral.com/profiles/blogs/random-ized-forest-thought-vectors-to-build-a-new-class-of Not so new as the author of the article says it is.
  18. Some basic advice on getting published in journals: https://www.insidehighered.com/advice/2016/04/21/advice-getting-published-scholarly-journal-essay 
  19. How machine learning is needed in computer security: http://www.datanami.com/2016/04/21/machine-learning-can-applied-cyber-security/ 
  20. Has this startup made an AI that passes the Turing test? http://techemergence.com/x-ai-says-their-ai-passed-the-turing-test/ 
  21. The incredible growth of R: http://www.techrepublic.com/article/exponential-growth-of-rs-open-source-community-threatens-commercial-competitors/