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Dm ml study_roadmap

Kang Pilsung
Kang Pilsung

This document provides a summary of study resources for data mining and machine learning, including: - A roadmap that classifies books by difficulty level from prerequisite to advanced PhD level. - Recommended books for each level, including original English versions and Korean translations when available. PDF versions and lecture videos are referenced. - Online learning platforms like Coursera and edX that offer free machine learning courses, as well as YouTube channels and individual instructors. - Interactive learning sites for practicing R and Python, including Codecademy, Datacamp and online Python tutors. - Additional websites providing tutorials, quick references, and packages for data mining algorithms.

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Study Roadmap & Resources for Data Mining & Machine Learning Ver. 0.12 Pilsung Kang Seoul National University of Science andTechnology pskang at seoultech dot ac dot kr 2014. 12. 22
Study Roadmap 覿: 覓伎 螻給襯 企覿 伎 ? 覈: 豈れ 企襯 覿襯企慨
Prerequisite Beginner Intermediate Advanced (for MS) Advanced (for Ph.D) DM & ML Theoretical Foundations Statistical Learning R Python
Resources: Books 覿: 豈れ 覲企ゼ 覲伎 覈: 覯覲語 ? PDF襦 れ伎? 螳譬襭?
Books: Prerequisite : Introduction to Mathematical Statistics (7th Ed.), R.V. Hogg, J. Mckean, A.T. Craig, Pearson, 2012. 覯覲: 襴糾 螳襦, 覦 蟾, 蟆暑語, 2012. : R Cookbook, P. Teetor, OReilly Cookbooks, 2011. 覯覲: R Cookbook, 伎 蟾, 語危, 2012. : Python for Data Analysis: Data Wrangling with Pandas, NumPy, and Ipython, W. McKinney, OReilly Media, 2012. 覯覲: 伎 殊企襴襯 一危 覿, 蟾蠏 蟾, 觜覩碁, 2013.
Books: Beginner : Data Mining for Business Intelligence: Concepts, Techniques, and Applications in MS Office Excel with XLMiner (2nd Ed.), G. Shmueli, N.R. Patel, P.C. Bruce, Wiley, 2010. Book website: http://www.dataminingbook.com/ 覯覲: 觜讀 誤襴るゼ 一危磯企, 譟一 蟾, 伎る, 2012. : An Introduction to Statistical Learning with Applications in R, G. James, D. witten, T. Hastie, R. Tibshirani Book website: http://www-bcf.usc.edu/~gareth/ISL/ (can download the book PDF) Lecture videos: http://www.dataschool.io/15-hours-of-expert-machine-learning-videos/ 蟲企: R 伎 一危磯企, 覦谿曙 讌, 蟲一, 2011. : Building Machine Learning Systems with Python, W. Richert, L.P. Coelho, Packt Publishing, 2013.
Books: Intermediate : Data Mining: Concepts and Techniques (3rd Ed.), J. Han, M. Kamber, J. Pei, Morgan Kaufmann, 2011. Book website: http://web.engr.illinois.edu/~hanj/bk3/bk3_slidesindex.htm 覯覲: 一危磯企 蠍磯螻 蠍磯 (2): 螳谿曙 蟾, Morgan Kaufmann, 2007. : Introduction to Data Mining, P.-N. Tan, M. Steinbach, V. Kumar, Addison-Wesley, 2005. Book website: http://www-users.cs.umn.edu/~kumar/dmbook/index.php 覯覲: 一危磯企: 蟾, 誤朱磯, 2007. : The Elements of Statistical Learning: Data Mining, Inference, and Prediction (2nd Ed.), Springer, 2011. Book website: http://statweb.stanford.edu/~tibs/ElemStatLearn/ (can download book PDF) : Machine Learning with R, Brett Lantz, Packt Publishing, 2013. : Machine Learning in Action, P. Harrington, Manning Publications, 2012. 覯覲: 襾語 ′: 蠍郁 螻襴讀朱 一危 襷企蠍, 蟾讌 蟾, 危, 2013.
Books: Advanced (for MS Students) : Pattern Classification (2nd Ed.), R.O. Duda, P.E. Hart, D.G. Stork, Wiley, 2001. Book pdf: http://cns-classes.bu.edu/cn550/Readings/duda-etal-00.pdf 覯覲: 伎語 (2), 譴 蟾, 危一, 2006. : Bayesian Artificial Intelligence (2nd Ed.), K.B. Korb, A.E. Nicholson, CRC Press, 2010. Book website: http://www.csse.monash.edu.au/bai/book/about.php
Books: Advanced (for Ph.D Students) : Pattern Recognition and Machine Learning, C.M. Bishop, Springer 2007. Book website: http://research.microsoft.com/en-us/um/people/cmbishop/PRML/ : Machine Learning: A Probabilistic Perspective, K.P. Murphy, MIT Press, 2012. Book website: http://www.cs.ubc.ca/~murphyk/MLbook/ : Probabilistic Graphical Models: Principles and Techniques, D. Koller, N. Friedman, MIT Press, 2009 Book website: http://pgm.stanford.edu/ Coursera Lecture: https://www.coursera.org/course/pgm : Building Probabilistic Graphical Models with Python, K.R. Karkera, Packt Publishing, 2014. Book website: http://statweb.stanford.edu/~tibs/ElemStatLearn/ (can download book PDF)
Resources: R & Python 覿: 企 る 企慨 覈: る慨覲企 襷一り ｸ る
Interactive Learning Sites for R 1. Datacamp: www.datacamp.com 2. Code school: https://www.codeschool.com/courses/try-r 3. swrl: http://www.swirlstats.com/ Other websites: http://www.cyclismo.org/tutorial/R/index.html: R 蠍一 覓碁 豢 http://www.rdatamining.com/ Data Mining 覦覯襦 譯 http://caret.r-forge.r-project.org/ 蠍磯蓋 DM/ML 螻襴讀 覿覿 螻 http://www.r-tutor.com/ R 伎 GPU computing 襭螳
Interactive Learning Sites for Python 1. Codecademy: http://www.codecademy.com/learn 2. Bento: https://www.bento.io/ 3. Online Python Tutor http://www.pythontutor.com/ Other websites: https://developers.google.com/edu/python/ Google 螻牛 Python 蠍一 螳譬 http://doc.pyschools.com/html/index.html Python quick reference guide http://www.pythonforbeginners.com/basics/python-websites-tutorials れ tutorial 襷 螻 http://scikit-learn.org/stable/ 蠍磯蓋 DM/ML 螻襴讀 覿覿 螻
Resources: Online Learning 覿: 豈襷 覺 危願 覈: 蠏朱 蟲 螳譬 覲襦
Online Learning Sites 1. Coursera: https://www.coursera.org/ 讌蠍 蟇 (1) 螳 (2) Listening ル 2. edX: https://www.edx.org/
Online Learning Sites 3. iTunes University: iPhone/iPad/Mac る PC襦 螳ロ 4. Youtube: 譯殊 襷 螳譬襯 螻朱ｌ. Example: Hugo Larochelle Neural Network 螳譬 Website: http://info.usherbrooke.ca/hlarochelle/neural_networks/content.html Hugo Larochelle Assistant Professor at CS of Universite de Sherbrooke Ph.D Supervisor: Yoshua Bengio Post-Doc Supervisor: Geoffrey Hinton Deep learning 願概 麹蟆??
Online Learning Sites 5. Metacademy: http://www.metacademy.org/roadmaps/

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Dm ml study_roadmap

  • 1. Study Roadmap & Resources for Data Mining & Machine Learning Ver. 0.12 Pilsung Kang Seoul National University of Science andTechnology pskang at seoultech dot ac dot kr 2014. 12. 22
  • 2. Study Roadmap 覿: 覓伎 螻給襯 企覿 伎 ? 覈: 豈れ 企襯 覿襯企慨
  • 3. Prerequisite Beginner Intermediate Advanced (for MS) Advanced (for Ph.D) DM & ML Theoretical Foundations Statistical Learning R Python
  • 4. Resources: Books 覿: 豈れ 覲企ゼ 覲伎 覈: 覯覲語 ? PDF襦 れ伎? 螳譬襭?
  • 5. Books: Prerequisite : Introduction to Mathematical Statistics (7th Ed.), R.V. Hogg, J. Mckean, A.T. Craig, Pearson, 2012. 覯覲: 襴糾 螳襦, 覦 蟾, 蟆暑語, 2012. : R Cookbook, P. Teetor, OReilly Cookbooks, 2011. 覯覲: R Cookbook, 伎 蟾, 語危, 2012. : Python for Data Analysis: Data Wrangling with Pandas, NumPy, and Ipython, W. McKinney, OReilly Media, 2012. 覯覲: 伎 殊企襴襯 一危 覿, 蟾蠏 蟾, 觜覩碁, 2013.
  • 6. Books: Beginner : Data Mining for Business Intelligence: Concepts, Techniques, and Applications in MS Office Excel with XLMiner (2nd Ed.), G. Shmueli, N.R. Patel, P.C. Bruce, Wiley, 2010. Book website: http://www.dataminingbook.com/ 覯覲: 觜讀 誤襴るゼ 一危磯企, 譟一 蟾, 伎る, 2012. : An Introduction to Statistical Learning with Applications in R, G. James, D. witten, T. Hastie, R. Tibshirani Book website: http://www-bcf.usc.edu/~gareth/ISL/ (can download the book PDF) Lecture videos: http://www.dataschool.io/15-hours-of-expert-machine-learning-videos/ 蟲企: R 伎 一危磯企, 覦谿曙 讌, 蟲一, 2011. : Building Machine Learning Systems with Python, W. Richert, L.P. Coelho, Packt Publishing, 2013.
  • 7. Books: Intermediate : Data Mining: Concepts and Techniques (3rd Ed.), J. Han, M. Kamber, J. Pei, Morgan Kaufmann, 2011. Book website: http://web.engr.illinois.edu/~hanj/bk3/bk3_slidesindex.htm 覯覲: 一危磯企 蠍磯螻 蠍磯 (2): 螳谿曙 蟾, Morgan Kaufmann, 2007. : Introduction to Data Mining, P.-N. Tan, M. Steinbach, V. Kumar, Addison-Wesley, 2005. Book website: http://www-users.cs.umn.edu/~kumar/dmbook/index.php 覯覲: 一危磯企: 蟾, 誤朱磯, 2007. : The Elements of Statistical Learning: Data Mining, Inference, and Prediction (2nd Ed.), Springer, 2011. Book website: http://statweb.stanford.edu/~tibs/ElemStatLearn/ (can download book PDF) : Machine Learning with R, Brett Lantz, Packt Publishing, 2013. : Machine Learning in Action, P. Harrington, Manning Publications, 2012. 覯覲: 襾語 ′: 蠍郁 螻襴讀朱 一危 襷企蠍, 蟾讌 蟾, 危, 2013.
  • 8. Books: Advanced (for MS Students) : Pattern Classification (2nd Ed.), R.O. Duda, P.E. Hart, D.G. Stork, Wiley, 2001. Book pdf: http://cns-classes.bu.edu/cn550/Readings/duda-etal-00.pdf 覯覲: 伎語 (2), 譴 蟾, 危一, 2006. : Bayesian Artificial Intelligence (2nd Ed.), K.B. Korb, A.E. Nicholson, CRC Press, 2010. Book website: http://www.csse.monash.edu.au/bai/book/about.php
  • 9. Books: Advanced (for Ph.D Students) : Pattern Recognition and Machine Learning, C.M. Bishop, Springer 2007. Book website: http://research.microsoft.com/en-us/um/people/cmbishop/PRML/ : Machine Learning: A Probabilistic Perspective, K.P. Murphy, MIT Press, 2012. Book website: http://www.cs.ubc.ca/~murphyk/MLbook/ : Probabilistic Graphical Models: Principles and Techniques, D. Koller, N. Friedman, MIT Press, 2009 Book website: http://pgm.stanford.edu/ Coursera Lecture: https://www.coursera.org/course/pgm : Building Probabilistic Graphical Models with Python, K.R. Karkera, Packt Publishing, 2014. Book website: http://statweb.stanford.edu/~tibs/ElemStatLearn/ (can download book PDF)
  • 10. Resources: R & Python 覿: 企 る 企慨 覈: る慨覲企 襷一り ｸ る
  • 11. Interactive Learning Sites for R 1. Datacamp: www.datacamp.com 2. Code school: https://www.codeschool.com/courses/try-r 3. swrl: http://www.swirlstats.com/ Other websites: http://www.cyclismo.org/tutorial/R/index.html: R 蠍一 覓碁 豢 http://www.rdatamining.com/ Data Mining 覦覯襦 譯 http://caret.r-forge.r-project.org/ 蠍磯蓋 DM/ML 螻襴讀 覿覿 螻 http://www.r-tutor.com/ R 伎 GPU computing 襭螳
  • 12. Interactive Learning Sites for Python 1. Codecademy: http://www.codecademy.com/learn 2. Bento: https://www.bento.io/ 3. Online Python Tutor http://www.pythontutor.com/ Other websites: https://developers.google.com/edu/python/ Google 螻牛 Python 蠍一 螳譬 http://doc.pyschools.com/html/index.html Python quick reference guide http://www.pythonforbeginners.com/basics/python-websites-tutorials れ tutorial 襷 螻 http://scikit-learn.org/stable/ 蠍磯蓋 DM/ML 螻襴讀 覿覿 螻
  • 13. Resources: Online Learning 覿: 豈襷 覺 危願 覈: 蠏朱 蟲 螳譬 覲襦
  • 14. Online Learning Sites 1. Coursera: https://www.coursera.org/ 讌蠍 蟇 (1) 螳 (2) Listening ル 2. edX: https://www.edx.org/
  • 15. Online Learning Sites 3. iTunes University: iPhone/iPad/Mac る PC襦 螳ロ 4. Youtube: 譯殊 襷 螳譬襯 螻朱ｌ. Example: Hugo Larochelle Neural Network 螳譬 Website: http://info.usherbrooke.ca/hlarochelle/neural_networks/content.html Hugo Larochelle Assistant Professor at CS of Universite de Sherbrooke Ph.D Supervisor: Yoshua Bengio Post-Doc Supervisor: Geoffrey Hinton Deep learning 願概 麹蟆??
  • 16. Online Learning Sites 5. Metacademy: http://www.metacademy.org/roadmaps/