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Machine Learning Essentials (dsth Meetup#3)

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Machine Learning Essentials
For Data Science Thailand Meetup #3
www.datascienceth.com
facebook.com/datascienceth
Komes Chandavimol

Published in: Data & Analytics
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Machine Learning Essentials (dsth Meetup#3)

  1. 1. Machine  Learning  Essentials   Data  Science  Thailand  Meetup#3   @Ne8T   17  December  2015   โกเมษ​ จันทวิมล. Komes  Chandavimol   komes@datascienceth.com   http://www.cs.toronto.edu/~urtasun/courses/CSC411/CSC411_Fall15_files/ machine_learning.jpg  
  2. 2. 2   http://www.adweek.com/prnewser/how-­‐many-­‐times-­‐do-­‐the-­‐worlds-­‐social-­‐media-­‐users-­‐click-­‐every-­‐minute/117427   https://www.domo.com/learn/data-­‐never-­‐sleeps-­‐3-­‐0  
  3. 3. Big  Data  Growth   3  
  4. 4. http://www.wired.com/insights/2014/07/data-­‐new-­‐oil-­‐digital-­‐economy/  
  5. 5. Big  Data  w/o  Algo   “Data  is  inherently  dumb.  It  doesn’t  actually  do  anything  unless  you  know  how  to  use  it;  how  to  act  with  it,”  Mr.  Sondergaard   “Algorithms  are  where  the  real  value  lies.  Algorithms  define  action.  Dynamic  algorithms  are  the  core  of  new  customer  interactions.”   “The  algorithmic  economy  will  power  the  next  great  leap  in  machine-­‐to-­‐machine  evolution  in  the  Internet  of  Things,   “Products  and  services  will  be  defined  by  the  sophistication  of  their  algorithms  and  services.  Organizations  will  be  valued,  not  just  on   their  big  data,  but  the  algorithms  that  turn  that  data  into  actions,  and  ultimately  impact  customers.   http://www.zdnet.com/article/big-­‐data-­‐is-­‐useless-­‐without-­‐algorithms-­‐gartner-­‐says/
  6. 6. ML   Machine  learning  is  a  core,  transformative  way  by  which  we’re   rethinking  everything  we’re  doing.  We’re  thoughtfully  applying  it   across  all  our  products,  be  it  search,  ads,  YouTube  or  Play     Sundar  Pichai,  CEO,  Google  
  7. 7. The  field  of  study  that  gives  computers  the  ability  to  learn   without  being  explicitly  programmed.”  Arthur  Samuel  (1990)     Improving  Performance  in  some  Task  with  Experience”.  Tom   Mitchell Tom  Mitchell  (1998)     Machine  Learning  deals  with  systems  that  can  learn  from  data.   What  is  Machine  Learning?   http://nkonst.com/machine-­‐learning-­‐explained-­‐simple-­‐words/   Wikipedia  
  8. 8. Workflow   http://nkonst.com/machine-­‐learning-­‐explained-­‐simple-­‐words/    
  9. 9. Data New Analytic Insights (Information, knowledge, data story) Data Product + VisualizationMass Analytic Tools Recommender systems Machine Learning Complex Event Processing Data Science Team Data ScientistPicture:http://www.clipartpanda.com/categories/scientist-clip-art Where is ML in Data Science? Doing Data Science by O'Neil et al (2013) DatascienceTh.com Datafication
  10. 10. The  Application  of  ML   Amazon.com,  netflix.com,  facebook.com  
  11. 11. Fraud  Detection   https://www.mapr.com/blog/new-­‐age-­‐fraud-­‐analytics-­‐machine-­‐learning-­‐hadoop   Skytree  
  12. 12. *  Personal  Assistants  (Siri)   *  Adorable  robots  (Jibo)   *  Dinosoir  Toy  (Watson)   *  DeepFace   The  Application  of  ML   https://cognitoys.com/#  
  13. 13. ML  in  Healthcare   Reference:  Grenplum,  vmware,  emc2    
  14. 14. ML  in  Finance   https://www.mapr.com/blog/new-­‐age-­‐fraud-­‐analytics-­‐machine-­‐learning-­‐hadoop   Skytree  
  15. 15. ML  at  Yahoo   http://www.slideshare.net/Hadoop_Summit/surge-­‐rise-­‐of-­‐scalable-­‐machine-­‐learning-­‐at-­‐yahoo  
  16. 16. ML  in  Retail   http://www.slideshare.net/sushantshankar1/ml-­‐meetup-­‐20150130-­‐presentation  
  17. 17. http://www.analyticsvidhya.com/blog/2015/11/infographic-­‐rise-­‐machine-­‐learning-­‐year-­‐2015/  
  18. 18. http://www.analyticsvidhya.com/blog/2015/11/infographic-­‐rise-­‐machine-­‐learning-­‐year-­‐2015/  
  19. 19. http://www.analyticsvidhya.com/blog/2015/11/infographic-­‐rise-­‐machine-­‐learning-­‐year-­‐2015/  
  20. 20. Oct   http://www.analyticsvidhya.com/blog/2015/11/infographic-­‐rise-­‐machine-­‐learning-­‐year-­‐2015/  
  21. 21. R,Python,  Weka   Excel   Armadillo  C++   Scilkit  Learn  for  python     Machine  Learning  Tools   Google  TensorFlow   Twitter  Dimsum   Airbnb  AeroSolve   Facebook  Torch  (deep  learning)   Linkedin  FeatureFu     Microsoft  Azure  ML   Google  Prediction  API   Amazon  ML   IBM  Watson  Analytics     Spunk  ML   SAP  Predictive  Analytics   SAS  SPSS   Rapid  Miner  
  22. 22. Landscape  

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